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ORCIDSamuel Kaski
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- affiliation: Aalto University, Finland
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2020 – today
- 2024
[j112]Janosch Menke
, Yasmine Nahal, Esben Jannik Bjerrum, Mikhail Kabeshov, Samuel Kaski, Ola Engkvist:
Metis: a python-based user interface to collect expert feedback for generative chemistry models. J. Cheminformatics 16(1): 100 (2024)- [j111]Lukas Prediger, Joonas Jälkö, Antti Honkela, Samuel Kaski:
Collaborative learning from distributed data with differentially private synthetic data. BMC Medical Informatics Decis. Mak. 24(1): 167 (2024) - [j110]Alexander Aushev, Thong Tran, Henri Pesonen, Andrew Howes, Samuel Kaski:
Likelihood-free inference in state-space models with unknown dynamics. Stat. Comput. 34(1): 27 (2024) - [j109]Zeinab R. Yousefi, Vuong Thanh Tung, Marie Al-Ghossein, Tuukka Ruotsalo, Giulio Jacucci, Samuel Kaski:
Entity Footprinting: Modeling Contextual User States via Digital Activity Monitoring. ACM Trans. Interact. Intell. Syst. 14(2): 9 (2024) - [j108]Louis Filstroff, Iiris Sundin, Petrus Mikkola, Aleksei Tiulpin, Juuso Kylmäoja, Samuel Kaski:
Targeted Active Learning for Bayesian Decision-Making. Trans. Mach. Learn. Res. 2024 (2024) - [c164]Manuel Haussmann, Tran Minh Son Le, Viivi Halla-aho, Samu Kurki, Jussi Leinonen, Miika Koskinen, Samuel Kaski, Harri Lähdesmäki:
Estimating treatment effects from single-arm trials via latent-variable modeling. AISTATS 2024: 2926-2934 - [c163]Robert T. Loftin, Mustafa Mert Çelikok, Herke van Hoof, Samuel Kaski, Frans A. Oliehoek:
Uncoupled Learning of Differential Stackelberg Equilibria with Commitments. AAMAS 2024: 1265-1273 - [c162]Yasmine Nahal, Markus Heinonen, Mikhail Kabeshov, Jon Paul Janet, Eva Nittinger, Ola Engkvist, Samuel Kaski:
Towards Interpretable Models of Chemist Preferences for Human-in-the-Loop Assisted Drug Discovery. AIDD@ICANN 2024: 58-70 - [c161]Muhammad Arslan Masood, Samuel Kaski, Hugo Ceulemans, Dorota Herman, Markus Heinonen:
Balancing Imbalanced Toxicity Models: Using MolBERT with Focal Loss. AIDD@ICANN 2024: 82-97 - [c160]Muhammad Arslan Masood, Tianyu Cui, Samuel Kaski:
Deep Bayesian Experimental Design for Drug Discovery. AIDD@ICANN 2024: 149-159 - [c159]Trung Q. Trinh, Markus Heinonen, Luigi Acerbi, Samuel Kaski:
Input-gradient space particle inference for neural network ensembles. ICLR 2024 - [c158]Tiago da Silva, Luiz Max Carvalho, Amauri H. Souza, Samuel Kaski, Diego Mesquita:
Embarrassingly Parallel GFlowNets. ICML 2024 - [c157]Jianhong Wang, Yang Li, Yuan Zhang, Wei Pan, Samuel Kaski:
Open Ad Hoc Teamwork with Cooperative Game Theory. ICML 2024 - [i121]Jianhong Wang, Yang Li, Yuan Zhang, Wei Pan, Samuel Kaski:
Open Ad Hoc Teamwork with Cooperative Game Theory. CoRR abs/2402.15259 (2024) - [i120]Shibei Zhu, Tran Nguyen Le, Samuel Kaski, Ville Kyrki:
Online Learning of Human Constraints from Feedback in Shared Autonomy. CoRR abs/2403.02974 (2024) - [i119]Ali Khoshvishkaie, Petrus Mikkola, Pierre-Alexandre Murena, Samuel Kaski:
Cooperative Bayesian Optimization for Imperfect Agents. CoRR abs/2403.04442 (2024) - [i118]Erik Nascimento, Diego Mesquita, Samuel Kaski, Amauri H. Souza:
In-n-Out: Calibrating Graph Neural Networks for Link Prediction. CoRR abs/2403.04605 (2024) - [i117]Marshal Arijona Sinaga, Julien Martinelli, Vikas Garg, Samuel Kaski:
Heteroscedastic Preferential Bayesian Optimization with Informative Noise Distributions. CoRR abs/2405.14657 (2024) - [i116]Anjie Liu, Jianhong Wang, Haoxuan Li, Xu Chen, Jun Wang, Samuel Kaski, Mengyue Yang:
Attaining Human's Desirable Outcomes in Human-AI Interaction via Structural Causal Games. CoRR abs/2405.16588 (2024) - [i115]Minttu Alakuijala, Reginald McLean, Isaac Woungang, Nariman Farsad, Samuel Kaski, Pekka Marttinen, Kai Yuan:
Video-Language Critic: Transferable Reward Functions for Language-Conditioned Robotics. CoRR abs/2405.19988 (2024) - [i114]Tiago da Silva, Luiz Max Carvalho, Amauri H. Souza, Samuel Kaski, Diego Mesquita:
Embarrassingly Parallel GFlowNets. CoRR abs/2406.03288 (2024) - [i113]Trung Trinh, Markus Heinonen, Luigi Acerbi, Samuel Kaski:
Improving robustness to corruptions with multiplicative weight perturbations. CoRR abs/2406.16540 (2024) - [i112]Stephen Menary, Samuel Kaski, Andre Freitas:
Transformer Normalisation Layers and the Independence of Semantic Subspaces. CoRR abs/2406.17837 (2024) - [i111]Rafal Karczewski, Samuel Kaski, Markus Heinonen, Vikas Garg:
What Ails Generative Structure-based Drug Design: Too Little or Too Much Expressivity? CoRR abs/2408.06050 (2024) - [i110]Avirup Das, Rishabh Dev Yadav, Sihao Sun, Mingfei Sun, Samuel Kaski, Wei Pan:
DroneDiffusion: Robust Quadrotor Dynamics Learning with Diffusion Models. CoRR abs/2409.11292 (2024) - 2023
- [j107]Sebastiaan De Peuter, Antti Oulasvirta, Samuel Kaski:
Toward AI assistants that let designers design. AI Mag. 44(1): 85-96 (2023) - [j106]Sophie Wharrie, Zhiyu Yang, Vishnu Raj, Remo Monti, Rahul Gupta, Ying Wang, Alicia Martin, Luke J. O'Connor, Samuel Kaski, Pekka Marttinen, Pier Francesco Palamara, Christoph Lippert, Andrea Ganna:
HAPNEST: efficient, large-scale generation and evaluation of synthetic datasets for genotypes and phenotypes. Bioinform. 39(9) (2023) - [j105]Ira R. J. Hebold Haraldsen, Christoffer Hatlestad-Hall, Camillo Marra, Hanna Renvall, Fernando Maestú, Jorge Acosta-Hernández, Soraya Alfonsin, Vebjørn Andersson, Abhilash Anand, Victor Ayllón, Aleksandar Babic, Asma Belhadi, Cindy Birck, Ricardo Bruña, Naike Caraglia, Claudia Carrarini, Erik Christensen, Americo Cicchetti, Signe Daugbjerg, Rossella Di Bidino, Ana Diaz-Ponce, Ainar Drews, Guido Maria Giuffrè, Jean Georges, Pedro Gil-Gregorio, Dianne Gove, Tim M. Govers, Harry Hallock, Marja Hietanen, Lone Holmen, Jaakko Hotta, Samuel Kaski, Rabindra Khadka, Antti S. Kinnunen, Anne M. Koivisto, Shrikanth Kulashekhar, Denis Larsen, Mia Liljeström, Pedro G. Lind, Alberto Marcos Dolado, Serena Elizabeth Marshall, Susanne Merz, Francesca Miraglia, Juha Montonen, Ville Mäntynen, Anne Rita Øksengård, Javier Olazarán, Teemu Paajanen, José M. Peña, Luís Peña, Daniel lrabien Peniche, Ana S. Pérez, Mohamed Radwan, Federico Ramírez-Toraño, Andrea Rodríguez-Pedrero, Timo Saarinen, Mario Salas-Carrillo, Riitta Salmelin, Sonia Sousa, Abdillah Suyuthi, Mathias Toft, Pablo Toharia, Thomas Tveitstøl, Mats Tveter, Ramesh Upreti, Robin J. Vermeulen, Fabrizio Vecchio, Anis Yazidi, Paolo Maria Rossini:
Intelligent digital tools for screening of brain connectivity and dementia risk estimation in people affected by mild cognitive impairment: the AI-Mind clinical study protocol. Frontiers Neurorobotics 17 (2023) - [j104]Mustafa Mert Çelikok, Pierre-Alexandre Murena, Samuel Kaski:
Modeling needs user modeling. Frontiers Artif. Intell. 6 (2023) - [j103]Nitin Williams, A. Ojanperä, Felix Siebenhühner, Benedetta Toselli, Satu Palva, Gabriele Arnulfo, Samuel Kaski, J. Matias Palva:
The influence of inter-regional delays in generating large-scale brain networks of phase synchronization. NeuroImage 279: 120318 (2023) - [j102]Zhirong Yang, Yuwei Chen, Denis Sedov, Samuel Kaski, Jukka Corander:
Stochastic cluster embedding. Stat. Comput. 33(1): 12 (2023) - [j101]Joonas Jälkö, Lukas Prediger, Antti Honkela, Samuel Kaski:
DPVIm: Differentially Private Variational Inference Improved. Trans. Mach. Learn. Res. 2023 (2023) - [c156]Mustafa Mert Çelikok, Pierre-Alexandre Murena, Samuel Kaski:
Teaching to Learn: Sequential Teaching of Learners with Internal States. AAAI 2023: 5939-5947 - [c155]Sebastiaan De Peuter, Samuel Kaski:
Zero-Shot Assistance in Sequential Decision Problems. AAAI 2023: 11551-11559 - [c154]Ossi Räisä, Joonas Jälkö, Samuel Kaski, Antti Honkela:
Noise-Aware Statistical Inference with Differentially Private Synthetic Data. AISTATS 2023: 3620-3643 - [c153]Petrus Mikkola, Julien Martinelli, Louis Filstroff, Samuel Kaski:
Multi-Fidelity Bayesian Optimization with Unreliable Information Sources. AISTATS 2023: 7425-7454 - [c152]Ayush Bharti, Masha Naslidnyk, Oscar Key, Samuel Kaski, François-Xavier Briol:
Optimally-weighted Estimators of the Maximum Mean Discrepancy for Likelihood-Free Inference. ICML 2023: 2289-2312 - [c151]Shibei Zhu, Rituraj Kaushik, Samuel Kaski, Ville Kyrki:
Imitation-Guided Multimodal Policy Generation from Behaviourally Diverse Demonstrations. IROS 2023: 1675-1682 - [c150]Sophie Wharrie, Zhiyu Yang, Andrea Ganna, Samuel Kaski:
Characterizing personalized effects of family information on disease risk using graph representation learning. MLHC 2023: 824-845 - [c149]Timur Garipov, Sebastiaan De Peuter, Ge Yang, Vikas Garg, Samuel Kaski, Tommi S. Jaakkola:
Compositional Sculpting of Iterative Generative Processes. NeurIPS 2023 - [c148]Daolang Huang, Ayush Bharti, Amauri H. Souza, Luigi Acerbi, Samuel Kaski:
Learning Robust Statistics for Simulation-based Inference under Model Misspecification. NeurIPS 2023 - [c147]Daolang Huang, Manuel Haussmann, Ulpu Remes, St John, Grégoire Clarté, Kevin Sebastian Luck, Samuel Kaski, Luigi Acerbi:
Practical Equivariances via Relational Conditional Neural Processes. NeurIPS 2023 - [c146]Ali Khoshvishkaie, Petrus Mikkola, Pierre-Alexandre Murena, Samuel Kaski:
Cooperative Bayesian Optimization for Imperfect Agents. ECML/PKDD (1) 2023: 475-490 - [c145]Alex Hämäläinen, Mustafa Mert Çelikok, Samuel Kaski:
Differentiable user models. UAI 2023: 798-808 - [i109]Robert Tyler Loftin, Mustafa Mert Çelikok, Herke van Hoof, Samuel Kaski, Frans A. Oliehoek:
Uncoupled Learning of Differential Stackelberg Equilibria with Commitments. CoRR abs/2302.03438 (2023) - [i108]Alexander Aushev, Aini Putkonen, Gregoire Clarte, Suyog Chandramouli, Luigi Acerbi, Samuel Kaski, Andrew Howes:
Online simulator-based experimental design for cognitive model selection. CoRR abs/2303.02227 (2023) - [i107]Alexander V. Nikitin, Letizia Iannucci, Samuel Kaski:
TSGM: A Flexible Framework for Generative Modeling of Synthetic Time Series. CoRR abs/2305.11567 (2023) - [i106]Julien Martinelli, Ayush Bharti, S. T. John, Armi Tiihonen, Sabina Sloman, Louis Filstroff, Samuel Kaski:
Cost-aware learning of relevant contextual variables within Bayesian optimization. CoRR abs/2305.14120 (2023) - [i105]Daolang Huang, Ayush Bharti, Amauri H. Souza, Luigi Acerbi, Samuel Kaski:
Learning Robust Statistics for Simulation-based Inference under Model Misspecification. CoRR abs/2305.15871 (2023) - [i104]Trung Q. Trinh, Markus Heinonen, Luigi Acerbi, Samuel Kaski:
Input gradient diversity for neural network ensembles. CoRR abs/2306.02775 (2023) - [i103]Daolang Huang, Manuel Haussmann, Ulpu Remes, S. T. John, Grégoire Clarté, Kevin Sebastian Luck, Samuel Kaski, Luigi Acerbi:
Practical Equivariances via Relational Conditional Neural Processes. CoRR abs/2306.10915 (2023) - [i102]Lukas Prediger, Joonas Jälkö, Antti Honkela, Samuel Kaski:
Collaborative Learning From Distributed Data With Differentially Private Synthetic Twin Data. CoRR abs/2308.04755 (2023) - [i101]Tiago da Silva, Eliezer S. Silva, Adèle H. Ribeiro, António Góis, Dominik Heider, Samuel Kaski, Diego Mesquita:
Human-in-the-Loop Causal Discovery under Latent Confounding using Ancestral GFlowNets. CoRR abs/2309.12032 (2023) - [i100]Timur Garipov, Sebastiaan De Peuter, Ge Yang, Vikas Garg, Samuel Kaski, Tommi S. Jaakkola:
Compositional Sculpting of Iterative Generative Processes. CoRR abs/2309.16115 (2023) - [i99]Quentin Bouniot, Ievgen Redko, Anton Mallasto, Charlotte Laclau, Karol Arndt, Oliver Struckmeier, Markus Heinonen, Ville Kyrki, Samuel Kaski:
Understanding deep neural networks through the lens of their non-linearity. CoRR abs/2310.11439 (2023) - [i98]Sophie Wharrie, Samuel Kaski:
Causal Similarity-Based Hierarchical Bayesian Models. CoRR abs/2310.12595 (2023) - [i97]Sabina J. Sloman, Ayush Bharti, Samuel Kaski:
The Fundamental Dilemma of Bayesian Active Meta-learning. CoRR abs/2310.14968 (2023) - [i96]Manuel Haussmann, Tran Minh Son Le, Viivi Halla-aho, Samu Kurki, Jussi Leinonen, Miika Koskinen, Samuel Kaski, Harri Lähdesmäki:
Estimating treatment effects from single-arm trials via latent-variable modeling. CoRR abs/2311.03002 (2023) - 2022
- [j100]Dovydas Kiciatovas, Qingli Guo, Miika Kailas, Henri Pesonen, Jukka Corander, Samuel Kaski, Esa Pitkänen, Ville Mustonen:
Identification of multiplicatively acting modulatory mutational signatures in cancer. BMC Bioinform. 23(1): 522 (2022) - [j99]Alexander Aushev, Henri Pesonen, Markus Heinonen, Jukka Corander, Samuel Kaski:
Likelihood-free inference with deep Gaussian processes. Comput. Stat. Data Anal. 174: 107529 (2022) - [j98]Iiris Sundin, Alexey Voronov, Haoping Xiao, Kostas Papadopoulos, Esben Jannik Bjerrum, Markus Heinonen, Atanas Patronov, Samuel Kaski, Ola Engkvist:
Human-in-the-loop assisted de novo molecular design. J. Cheminformatics 14(1): 86 (2022) - [j97]Lukas Prediger, Niki A. Loppi, Samuel Kaski, Antti Honkela:
d3p - A Python Package for Differentially-Private Probabilistic Programming. Proc. Priv. Enhancing Technol. 2022(2): 407-425 (2022) - [j96]Betül Güvenç Paltun, Samuel Kaski, Hiroshi Mamitsuka:
DIVERSE: Bayesian Data IntegratiVE Learning for Precise Drug ResponSE Prediction. IEEE ACM Trans. Comput. Biol. Bioinform. 19(4): 2197-2207 (2022) - [c144]Daniel Augusto de Souza, Diego Mesquita, Samuel Kaski, Luigi Acerbi:
Parallel MCMC Without Embarrassing Failures. AISTATS 2022: 1786-1804 - [c143]Alexander V. Nikitin, S. T. John, Arno Solin, Samuel Kaski:
Non-separable Spatio-temporal Graph Kernels via SPDEs. AISTATS 2022: 10640-10660 - [c142]Mustafa Mert Çelikok, Frans A. Oliehoek, Samuel Kaski:
Best-Response Bayesian Reinforcement Learning with Bayes-adaptive POMDPs for Centaurs. AAMAS 2022: 235-243 - [c141]Tung Thanh Vuong, Salvatore Andolina, Giulio Jacucci, Pedram Daee, Khalil Klouche, Mats Sjöberg, Tuukka Ruotsalo, Samuel Kaski:
EntityBot: Actionable Entity Recommendations for Everyday Digital Task. CHI Extended Abstracts 2022: 208:1-208:4 - [c140]Ayush Bharti, Louis Filstroff, Samuel Kaski:
Approximate Bayesian Computation with Domain Expert in the Loop. ICML 2022: 1893-1905 - [c139]Trung Q. Trinh, Markus Heinonen, Luigi Acerbi, Samuel Kaski:
Tackling covariate shift with node-based Bayesian neural networks. ICML 2022: 21751-21775 - [c138]Alexander V. Nikitin, Samuel Kaski:
Human-in-the-Loop Large-Scale Predictive Maintenance of Workstations. KDD 2022: 3682-3690 - [c137]Tianyu Cui, Yogesh Kumar, Pekka Marttinen, Samuel Kaski:
Deconfounded Representation Similarity for Comparison of Neural Networks. NeurIPS 2022 - [c136]Amauri H. Souza, Diego Mesquita, Samuel Kaski, Vikas Garg:
Provably expressive temporal graph networks. NeurIPS 2022 - [c135]Yogesh Verma, Samuel Kaski, Markus Heinonen, Vikas Garg:
Modular Flows: Differential Molecular Generation. NeurIPS 2022 - [c134]Pashupati Hegde, Çagatay Yildiz, Harri Lähdesmäki, Samuel Kaski, Markus Heinonen:
Variational multiple shooting for Bayesian ODEs with Gaussian processes. UAI 2022: 790-799 - [e4]Giulio Jacucci, Samuel Kaski, Cristina Conati, Simone Stumpf, Tuukka Ruotsalo, Krzysztof Gajos:
IUI 2022: 27th International Conference on Intelligent User Interfaces, Helsinki, Finland, March 22 - 25, 2022. ACM 2022, ISBN 978-1-4503-9144-3 [contents] - [e3]Giulio Jacucci, Samuel Kaski, Cristina Conati, Simone Stumpf, Tuukka Ruotsalo, Krzysztof Gajos:
IUI 2022: 27th International Conference on Intelligent User Interfaces, Helsinki, Finland, March 22 - 25, 2022 - Companion Volume. ACM 2022, ISBN 978-1-4503-9145-0 [contents] - [i95]Ayush Bharti, Louis Filstroff, Samuel Kaski:
Approximate Bayesian Computation with Domain Expert in the Loop. CoRR abs/2201.12090 (2022) - [i94]Tianyu Cui, Yogesh Kumar, Pekka Marttinen, Samuel Kaski:
Deconfounded Representation Similarity for Comparison of Neural Networks. CoRR abs/2202.00095 (2022) - [i93]Sebastiaan De Peuter, Samuel Kaski:
Zero-Shot Assistance in Novel Decision Problems. CoRR abs/2202.07364 (2022) - [i92]Daniel Augusto de Souza, Diego Mesquita, Samuel Kaski, Luigi Acerbi:
Parallel MCMC Without Embarrassing Failures. CoRR abs/2202.11154 (2022) - [i91]Mustafa Mert Çelikok, Frans A. Oliehoek, Samuel Kaski:
Best-Response Bayesian Reinforcement Learning with Bayes-adaptive POMDPs for Centaurs. CoRR abs/2204.01160 (2022) - [i90]Ossi Räisä, Joonas Jälkö, Samuel Kaski, Antti Honkela:
Noise-Aware Statistical Inference with Differentially Private Synthetic Data. CoRR abs/2205.14485 (2022) - [i89]Trung Q. Trinh, Markus Heinonen, Luigi Acerbi, Samuel Kaski:
Tackling covariate shift with node-based Bayesian neural networks. CoRR abs/2206.02435 (2022) - [i88]Alexander V. Nikitin, Samuel Kaski:
Human-in-the-Loop Large-Scale Predictive Maintenance of Workstations. CoRR abs/2206.11574 (2022) - [i87]Daolang Huang, Louis Filstroff, Petrus Mikkola, Runkai Zheng, Samuel Kaski:
Bayesian Optimization Augmented with Actively Elicited Expert Knowledge. CoRR abs/2208.08742 (2022) - [i86]Amauri H. Souza, Diego Mesquita, Samuel Kaski, Vikas Garg:
Provably expressive temporal graph networks. CoRR abs/2209.15059 (2022) - [i85]Yogesh Verma, Samuel Kaski, Markus Heinonen, Vikas Garg:
Modular Flows: Differential Molecular Generation. CoRR abs/2210.06032 (2022) - [i84]Petrus Mikkola, Julien Martinelli, Louis Filstroff, Samuel Kaski:
Multi-Fidelity Bayesian Optimization with Unreliable Information Sources. CoRR abs/2210.13937 (2022) - [i83]Joonas Jälkö, Lukas Prediger, Antti Honkela, Samuel Kaski:
DPVIm: Differentially Private Variational Inference Improved. CoRR abs/2210.15961 (2022) - [i82]Alex Hämäläinen, Mustafa Mert Çelikok, Samuel Kaski:
Differentiable User Models. CoRR abs/2211.16277 (2022) - 2021
- [j95]Betül Güvenç Paltun, Hiroshi Mamitsuka, Samuel Kaski:
Improving drug response prediction by integrating multiple data sources: matrix factorization, kernel and network-based approaches. Briefings Bioinform. 22(1): 346-359 (2021) - [j94]Betül Güvenç Paltun, Samuel Kaski, Hiroshi Mamitsuka:
Machine learning approaches for drug combination therapies. Briefings Bioinform. 22(6) (2021) - [j93]Joonas Jälkö, Eemil Lagerspetz, Jari Haukka, Sasu Tarkoma, Antti Honkela, Samuel Kaski:
Privacy-preserving data sharing via probabilistic modeling. Patterns 2(7): 100271 (2021) - [j92]Giulio Jacucci, Pedram Daee, Tung Thanh Vuong, Salvatore Andolina, Khalil Klouche, Mats Sjöberg, Tuukka Ruotsalo, Samuel Kaski:
Entity Recommendation for Everyday Digital Tasks. ACM Trans. Comput. Hum. Interact. 28(5): 29:1-29:41 (2021) - [c133]Anton Mallasto, Markus Heinonen, Samuel Kaski:
Bayesian Inference for Optimal Transport with Stochastic Cost. ACML 2021: 1601-1616 - [c132]Antti Keurulainen, Isak Westerlund, Ariel Kwiatkowski, Samuel Kaski, Alexander Ilin:
Behaviour-Conditioned Policies for Cooperative Reinforcement Learning Tasks. ICANN (4) 2021: 493-504 - [c131]Antti Keurulainen, Isak Westerlund, Samuel Kaski, Alexander Ilin:
Learning to Assist Agents by Observing Them. ICANN (4) 2021: 519-530 - [c130]Tejas Kulkarni, Joonas Jälkö, Antti Koskela, Samuel Kaski, Antti Honkela:
Differentially Private Bayesian Inference for Generalized Linear Models. ICML 2021: 5838-5849 - [c129]Alexander V. Nikitin, Samuel Kaski:
Decision Rule Elicitation for Domain Adaptation. IUI 2021: 244-248 - [c128]Zheyang Shen, Markus Heinonen, Samuel Kaski:
De-randomizing MCMC dynamics with the diffusion Stein operator. NeurIPS 2021: 17507-17517 - [c127]Vuong Thanh Tung, Salvatore Andolina, Giulio Jacucci, Pedram Daee, Khalil Klouche, Mats Sjöberg, Tuukka Ruotsalo, Samuel Kaski:
EntityBot: Supporting Everyday Digital Tasks with Entity Recommendations. RecSys 2021: 753-756 - [c126]Khaoula el Mekkaoui, Diego Mesquita, Paul Blomstedt, Samuel Kaski:
Federated stochastic gradient Langevin dynamics. UAI 2021: 1703-1712 - [i81]Alexander V. Nikitin, Samuel Kaski:
Decision Rule Elicitation for Domain Adaptation. CoRR abs/2102.11539 (2021) - [i80]Lukas Prediger, Niki A. Loppi, Samuel Kaski, Antti Honkela:
d3p - A Python Package for Differentially-Private Probabilistic Programming. CoRR abs/2103.11648 (2021) - [i79]Betül Güvenç Paltun, Samuel Kaski, Hiroshi Mamitsuka:
DIVERSE: bayesian Data IntegratiVE learning for precise drug ResponSE prediction. CoRR abs/2104.00520 (2021) - [i78]Anton Mallasto, Karol Arndt, Markus Heinonen, Samuel Kaski, Ville Kyrki:
Affine Transport for Sim-to-Real Domain Adaptation. CoRR abs/2105.11739 (2021) - [i77]Louis Filstroff, Iiris Sundin, Petrus Mikkola, Aleksei Tiulpin, Juuso Kylmäoja, Samuel Kaski:
Targeted Active Learning for Bayesian Decision-Making. CoRR abs/2106.04193 (2021) - [i76]Pashupati Hegde, Çagatay Yildiz, Harri Lähdesmäki, Samuel Kaski, Markus Heinonen:
Bayesian inference of ODEs with Gaussian processes. CoRR abs/2106.10905 (2021) - [i75]Sebastiaan De Peuter, Antti Oulasvirta, Samuel Kaski:
Toward AI Assistants That Let Designers Design. CoRR abs/2107.13074 (2021) - [i74]Zhirong Yang, Yuwei Chen, Denis Sedov, Samuel Kaski, Jukka Corander:
Stochastic Cluster Embedding. CoRR abs/2108.08003 (2021) - [i73]Antti Keurulainen, Isak Westerlund, Ariel Kwiatkowski, Samuel Kaski, Alexander Ilin:
Behaviour-conditioned policies for cooperative reinforcement learning tasks. CoRR abs/2110.01266 (2021) - [i72]Antti Keurulainen, Isak Westerlund, Samuel Kaski, Alexander Ilin:
Learning to Assist Agents by Observing Them. CoRR abs/2110.01311 (2021) - [i71]Zheyang Shen, Markus Heinonen, Samuel Kaski:
De-randomizing MCMC dynamics with the diffusion Stein operator. CoRR abs/2110.03768 (2021) - [i70]Tejas Kulkarni, Joonas Jälkö, Samuel Kaski, Antti Honkela:
Locally Differentially Private Bayesian Inference. CoRR abs/2110.14426 (2021) - [i69]Alexander Aushev, Thong Tran, Henri Pesonen, Andrew Howes, Samuel Kaski:
Likelihood-Free Inference in State-Space Models with Unknown Dynamics. CoRR abs/2111.01555 (2021) - [i68]Alexander V. Nikitin, S. T. John, Arno Solin, Samuel Kaski:
Non-separable Spatio-temporal Graph Kernels via SPDEs. CoRR abs/2111.08524 (2021) - 2020
- [j91]Tuukka Ruotsalo, Giulio Jacucci, Samuel Kaski:
Interactive faceted query suggestion for exploratory search: Whole-session effectiveness and interaction engagement. J. Assoc. Inf. Sci. Technol. 71(7): 742-756 (2020) - [j90]Homayun Afrabandpey, Tomi Peltola, Juho Piironen, Aki Vehtari, Samuel Kaski:
A decision-theoretic approach for model interpretability in Bayesian framework. Mach. Learn. 109(9-10): 1855-1876 (2020) - [j89]Jukka Sirén, Samuel Kaski:
Local dimension reduction of summary statistics for likelihood-free inference. Stat. Comput. 30(3): 559-570 (2020) - [c125]Jonathan Strahl, Jaakko Peltonen, Hiroshi Mamitsuka, Samuel Kaski:
Scalable Probabilistic Matrix Factorization with Graph-Based Priors. AAAI 2020: 5851-5858 - [c124]Zheyang Shen, Markus Heinonen, Samuel Kaski:
Learning spectrograms with convolutional spectral kernels. AISTATS 2020: 3826-3836 - [c123]Tianyu Cui, Pekka Marttinen, Samuel Kaski:
Learning Global Pairwise Interactions with Bayesian Neural Networks. ECAI 2020: 1087-1094 - [c122]Tom Vander Aa, Xiangju Qin, Paul Blomstedt, Roel Wuyts, Wilfried Verachtert, Samuel Kaski:
A High-Performance Implementation of Bayesian Matrix Factorization with Limited Communication. ICCS (6) 2020: 3-16 - [c121]Petrus Mikkola, Milica Todorovic, Jari Järvi, Patrick Rinke, Samuel Kaski:
Projective Preferential Bayesian Optimization. ICML 2020: 6884-6892 - [c120]Diego P. P. Mesquita, Amauri H. Souza Jr., Samuel Kaski:
Rethinking pooling in graph neural networks. NeurIPS 2020 - [c119]Fabio Colella, Pedram Daee, Jussi Jokinen, Antti Oulasvirta, Samuel Kaski:
Human Strategic Steering Improves Performance of Interactive Optimization. UMAP 2020: 293-297 - [i67]Petrus Mikkola, Milica Todorovic, Jari Järvi, Patrick Rinke, Samuel Kaski:
Projective Preferential Bayesian Optimization. CoRR abs/2002.03113 (2020) - [i66]Tianyu Cui, Aki S. Havulinna, Pekka Marttinen, Samuel Kaski:
Informative Gaussian Scale Mixture Priors for Bayesian Neural Networks. CoRR abs/2002.10243 (2020) - [i65]Yuxin Sun, Benny Chain, Samuel Kaski, John Shawe-Taylor:
Correlated Feature Selection with Extended Exclusive Group Lasso. CoRR abs/2002.12460 (2020) - [i64]Tom Vander Aa, Xiangju Qin, Paul Blomstedt, Roel Wuyts, Wilfried Verachtert, Samuel Kaski:
A High-Performance Implementation of Bayesian Matrix Factorization with Limited Communication. CoRR abs/2004.02561 (2020) - [i63]Khaoula el Mekkaoui, Diego P. P. Mesquita, Paul Blomstedt, Samuel Kaski:
Variance reduction for distributed stochastic gradient MCMC. CoRR abs/2004.11231 (2020) - [i62]Fabio Colella, Pedram Daee, Jussi Jokinen, Antti Oulasvirta, Samuel Kaski:
Human Strategic Steering Improves Performance of Interactive Optimization. CoRR abs/2005.01291 (2020) - [i61]Alexander Aushev, Henri Pesonen, Markus Heinonen, Jukka Corander, Samuel Kaski:
Likelihood-Free Inference with Deep Gaussian Processes. CoRR abs/2006.10571 (2020) - [i60]Mikko A. Heikkilä, Antti Koskela, Kana Shimizu, Samuel Kaski, Antti Honkela:
Differentially private cross-silo federated learning. CoRR abs/2007.05553 (2020) - [i59]Mustafa Mert Çelikok, Pierre-Alexandre Murena, Samuel Kaski:
Teaching to Learn: Sequential Teaching of Agents with Inner States. CoRR abs/2009.06227 (2020) - [i58]Razane Tajeddine, Joonas Jälkö, Samuel Kaski, Antti Honkela:
Privacy-preserving Data Sharing on Vertically Partitioned Data. CoRR abs/2010.09293 (2020) - [i57]Anton Mallasto, Markus Heinonen, Samuel Kaski:
Bayesian Inference for Optimal Transport with Stochastic Cost. CoRR abs/2010.09327 (2020) - [i56]Diego P. P. Mesquita, Amauri H. Souza Jr., Samuel Kaski:
Rethinking pooling in graph neural networks. CoRR abs/2010.11418 (2020) - [i55]Trung Q. Trinh, Samuel Kaski, Markus Heinonen:
Scalable Bayesian neural networks by layer-wise input augmentation. CoRR abs/2010.13498 (2020) - [i54]Tejas Kulkarni, Joonas Jälkö, Antti Koskela, Samuel Kaski, Antti Honkela:
Differentially Private Bayesian Inference for Generalized Linear Models. CoRR abs/2011.00467 (2020) - [i53]Charles W. L. Gadd, Markus Heinonen, Harri Lähdesmäki, Samuel Kaski:
Sample-efficient reinforcement learning using deep Gaussian processes. CoRR abs/2011.01226 (2020)
2010 – 2019
- 2019
- [j88]Teppo Mikael Niinimäki, Mikko A. Heikkilä, Antti Honkela, Samuel Kaski:
Representation transfer for differentially private drug sensitivity prediction. Bioinform. 35(14): i218-i224 (2019) - [j87]Héctor Climente-González, Chloé-Agathe Azencott, Samuel Kaski, Makoto Yamada:
Block HSIC Lasso: model-free biomarker detection for ultra-high dimensional data. Bioinform. 35(14): i427-i435 (2019) - [j86]Markus Heinonen, Maria Osmala, Henrik Mannerström, Janne Wallenius, Samuel Kaski, Juho Rousu, Harri Lähdesmäki:
Bayesian metabolic flux analysis reveals intracellular flux couplings. Bioinform. 35(14): i548-i557 (2019) - [j85]Jussi Gillberg, Pekka Marttinen, Hiroshi Mamitsuka, Samuel Kaski:
Modelling G×E with historical weather information improves genomic prediction in new environments. Bioinform. 35(20): 4045-4052 (2019) - [j84]Antti Kangasrääsiö, Jussi P. P. Jokinen, Antti Oulasvirta, Andrew Howes, Samuel Kaski:
Parameter Inference for Computational Cognitive Models with Approximate Bayesian Computation. Cogn. Sci. 43(6) (2019) - [j83]Giulio Jacucci, Oswald Barral, Pedram Daee, Markus Wenzel, Baris Serim, Tuukka Ruotsalo, Patrik Pluchino, Jonathan Freeman, Luciano Gamberini, Samuel Kaski, Benjamin Blankertz:
Integrating neurophysiologic relevance feedback in intent modeling for information retrieval. J. Assoc. Inf. Sci. Technol. 70(9): 917-930 (2019) - [j82]Xiangju Qin, Paul Blomstedt, Eemeli Leppäaho, Pekka Parviainen, Samuel Kaski:
Distributed Bayesian matrix factorization with limited communication. Mach. Learn. 108(10): 1805-1830 (2019) - [c118]Pashupati Hegde, Markus Heinonen, Harri Lähdesmäki, Samuel Kaski:
Deep learning with differential Gaussian process flows. AISTATS 2019: 1812-1821 - [c117]Zheyang Shen, Markus Heinonen, Samuel Kaski:
Harmonizable mixture kernels with variational Fourier features. AISTATS 2019: 3273-3282 - [c116]Iiris Sundin, Peter Schulam, Eero Siivola, Aki Vehtari, Suchi Saria, Samuel Kaski:
Active Learning for Decision-Making from Imbalanced Observational Data. ICML 2019: 6046-6055 - [c115]Homayun Afrabandpey, Tomi Peltola, Samuel Kaski:
Human-in-the-loop Active Covariance Learning for Improving Prediction in Small Data Sets. IJCAI 2019: 1959-1966 - [c114]Xiangju Qin, Paul Blomstedt, Samuel Kaski:
Scalable Bayesian Non-linear Matrix Completion. IJCAI 2019: 3275-3281 - [c113]Yao Lu, Zhirong Yang, Juho Kannala, Samuel Kaski:
Learning Image Relations with Contrast Association Networks. IJCNN 2019: 1-7 - [c112]Tomi Peltola, Mustafa Mert Çelikok, Pedram Daee, Samuel Kaski:
Machine Teaching of Active Sequential Learners. NeurIPS 2019: 11202-11213 - [c111]Kenneth Blomqvist, Samuel Kaski, Markus Heinonen:
Deep Convolutional Gaussian Processes. ECML/PKDD (2) 2019: 582-597 - [c110]Diego P. P. Mesquita, Paul Blomstedt, Samuel Kaski:
Embarrassingly Parallel MCMC using Deep Invertible Transformations. UAI 2019: 1244-1252 - [i52]Tianyu Cui, Pekka Marttinen, Samuel Kaski:
Recovering Pairwise Interactions Using Neural Networks. CoRR abs/1901.08361 (2019) - [i51]Teppo Mikael Niinimäki, Mikko A. Heikkilä, Antti Honkela, Samuel Kaski:
Representation Transfer for Differentially Private Drug Sensitivity Prediction. CoRR abs/1901.10227 (2019) - [i50]Homayun Afrabandpey, Tomi Peltola, Samuel Kaski:
Human-in-the-loop Active Covariance Learning for Improving Prediction in Small Data Sets. CoRR abs/1902.09834 (2019) - [i49]Diego P. P. Mesquita, Paul Blomstedt, Samuel Kaski:
Embarrassingly parallel MCMC using deep invertible transformations. CoRR abs/1903.04556 (2019) - [i48]Iiris Sundin, Peter Schulam, Eero Siivola, Aki Vehtari, Suchi Saria, Samuel Kaski:
Active Learning for Decision-Making from Imbalanced Observational Data. CoRR abs/1904.05268 (2019) - [i47]Zheyang Shen, Markus Heinonen, Samuel Kaski:
Learning spectrograms with convolutional spectral kernels. CoRR abs/1905.09917 (2019) - [i46]Xiangju Qin, Paul Blomstedt, Samuel Kaski:
Scalable Bayesian Non-linear Matrix Completion. CoRR abs/1908.01009 (2019) - [i45]Jonathan Strahl, Jaakko Peltonen, Hiroshi Mamitsuka, Samuel Kaski:
Scalable Probabilistic Matrix Factorization with Graph-Based Priors. CoRR abs/1908.09393 (2019) - [i44]Homayun Afrabandpey, Tomi Peltola, Juho Piironen, Aki Vehtari, Samuel Kaski:
Making Bayesian Predictive Models Interpretable: A Decision Theoretic Approach. CoRR abs/1910.09358 (2019) - [i43]Tomi Peltola, Jussi Jokinen, Samuel Kaski:
Probabilistic Formulation of the Take The Best Heuristic. CoRR abs/1911.00572 (2019) - [i42]Joonas Jälkö, Eemil Lagerspetz, Jari Haukka, Sasu Tarkoma, Samuel Kaski, Antti Honkela:
Privacy-preserving data sharing via probabilistic modelling. CoRR abs/1912.04439 (2019) - [i41]Mustafa Mert Çelikok, Tomi Peltola, Pedram Daee, Samuel Kaski:
Interactive AI with a Theory of Mind. CoRR abs/1912.05284 (2019) - 2018
- [j81]Iiris Sundin, Tomi Peltola, Luana Micallef, Homayun Afrabandpey, Marta Soare, Muntasir Mamun Majumder, Pedram Daee, Chen He, Baris Serim, Aki S. Havulinna, Caroline Heckman, Giulio Jacucci, Pekka Marttinen, Samuel Kaski:
Improving genomics-based predictions for precision medicine through active elicitation of expert knowledge. Bioinform. 34(13): i395-i403 (2018) - [j80]Jarno Lintusaari, Henri Vuollekoski, Antti Kangasrääsiö, Kusti Skytén, Marko Järvenpää, Pekka Marttinen, Michael U. Gutmann, Aki Vehtari, Jukka Corander, Samuel Kaski:
ELFI: Engine for Likelihood-Free Inference. J. Mach. Learn. Res. 19: 16:1-16:7 (2018) - [j79]Antti Kangasrääsiö, Samuel Kaski:
Inverse reinforcement learning from summary data. Mach. Learn. 107(8-10): 1517-1535 (2018) - [j78]Michael U. Gutmann, Ritabrata Dutta, Samuel Kaski, Jukka Corander:
Likelihood-free inference via classification. Stat. Comput. 28(2): 411-425 (2018) - [j77]Tuukka Ruotsalo, Jaakko Peltonen, Manuel J. A. Eugster, Dorota Glowacka, Patrik Floréen, Petri Myllymäki, Giulio Jacucci, Samuel Kaski:
Interactive Intent Modeling for Exploratory Search. ACM Trans. Inf. Syst. 36(4): 44:1-44:46 (2018) - [c109]Tomi Peltola, Jussi Jokinen, Samuel Kaski:
Probabilistic Formulation of the Take The Best Heuristic. CogSci 2018 - [c108]Pedram Daee, Tomi Peltola, Aki Vehtari, Samuel Kaski:
User Modelling for Avoiding Overfitting in Interactive Knowledge Elicitation for Prediction. IUI 2018: 305-310 - [c107]Pashupati Hegde, Markus Heinonen, Samuel Kaski:
Variational zero-inflated Gaussian processes with sparse kernels. UAI 2018: 361-371 - [i40]Markus Heinonen, Maria Osmala, Henrik Mannerström, Janne Wallenius, Samuel Kaski, Juho Rousu, Harri Lähdesmäki:
Bayesian Metabolic Flux Analysis reveals intracellular flux couplings. CoRR abs/1804.06673 (2018) - [i39]Tomi Peltola, Mustafa Mert Çelikok, Pedram Daee, Samuel Kaski:
Modelling User's Theory of AI's Mind in Interactive Intelligent Systems. CoRR abs/1809.02869 (2018) - [i38]Kenneth Blomqvist, Samuel Kaski, Markus Heinonen:
Deep convolutional Gaussian processes. CoRR abs/1810.03052 (2018) - [i37]Pashupati Hegde, Markus Heinonen, Harri Lähdesmäki, Samuel Kaski:
Deep learning with differential Gaussian process flows. CoRR abs/1810.04066 (2018) - [i36]Zheyang Shen, Markus Heinonen, Samuel Kaski:
Harmonizable mixture kernels with variational Fourier features. CoRR abs/1810.04416 (2018) - [i35]Charlie Rogers-Smith, Henri Pesonen, Samuel Kaski:
Approximate Bayesian Computation via Population Monte Carlo and Classification. CoRR abs/1810.12233 (2018) - [i34]Sami Remes, Markus Heinonen, Samuel Kaski:
Neural Non-Stationary Spectral Kernel. CoRR abs/1811.10978 (2018) - 2017
- [j76]Chen He, Luana Micallef, ZiaurRehman Tanoli, Samuel Kaski, Tero Aittokallio, Giulio Jacucci:
MediSyn: uncertainty-aware visualization of multiple biomedical datasets to support drug treatment selection. BMC Bioinform. 18(S-10): 393:1-393:12 (2017) - [j75]Pekka Parviainen, Samuel Kaski:
Learning structures of Bayesian networks for variable groups. Int. J. Approx. Reason. 88: 110-127 (2017) - [j74]Eemeli Leppäaho, Muhammad Ammad-ud-din, Samuel Kaski:
GFA: Exploratory Analysis of Multiple Data Sources with Group Factor Analysis. J. Mach. Learn. Res. 18: 39:1-39:5 (2017) - [j73]Sahely Bhadra, Samuel Kaski, Juho Rousu:
Multi-view kernel completion. Mach. Learn. 106(5): 713-739 (2017) - [j72]Pedram Daee, Tomi Peltola, Marta Soare, Samuel Kaski:
Knowledge elicitation via sequential probabilistic inference for high-dimensional prediction. Mach. Learn. 106(9-10): 1599-1620 (2017) - [c106]Sami Remes, Markus Heinonen, Samuel Kaski:
A Mutually-Dependent Hadamard Kernel for Modelling Latent Variable Couplings. ACML 2017: 455-470 - [c105]Makoto Yamada, Koh Takeuchi, Tomoharu Iwata, John Shawe-Taylor, Samuel Kaski:
Localized Lasso for High-Dimensional Regression. AISTATS 2017: 325-333 - [c104]Antti Kangasrääsiö, Kumaripaba Athukorala, Andrew Howes, Jukka Corander, Samuel Kaski, Antti Oulasvirta:
Inferring Cognitive Models from Data using Approximate Bayesian Computation. CHI 2017: 1295-1306 - [c103]Oswald Barral, Ilkka Kosunen, Tuukka Ruotsalo, Michiel M. A. Spapé, Manuel J. A. Eugster, Niklas Ravaja, Samuel Kaski, Giulio Jacucci:
BCI for Physiological Text Annotation. BCIforReal@IUI 2017: 9-13 - [c102]Luana Micallef, Iiris Sundin, Pekka Marttinen, Muhammad Ammad-ud-din, Tomi Peltola, Marta Soare, Giulio Jacucci, Samuel Kaski:
Interactive Elicitation of Knowledge on Feature Relevance Improves Predictions in Small Data Sets. IUI 2017: 547-552 - [c101]Makoto Yamada, Wenzhao Lian, Amit Goyal, Jianhui Chen, Kishan Wimalawarne, Suleiman A. Khan, Samuel Kaski, Hiroshi Mamitsuka, Yi Chang:
Convex Factorization Machine for Toxicogenomics Prediction. KDD 2017: 1215-1224 - [c100]Mikko A. Heikkilä, Eemil Lagerspetz, Samuel Kaski, Kana Shimizu, Sasu Tarkoma, Antti Honkela:
Differentially private Bayesian learning on distributed data. NIPS 2017: 3226-3235 - [c99]Sami Remes, Markus Heinonen, Samuel Kaski:
Non-Stationary Spectral Kernels. NIPS 2017: 4642-4651 - [c98]Pedram Daee, Tomi Peltola, Marta Soare, Samuel Kaski:
Probabilistic Expert Knowledge Elicitation of Feature Relevances in Sparse Linear Regression. IAL@PKDD/ECML 2017: 64-66 - [c97]Homayun Afrabandpey, Tomi Peltola, Samuel Kaski:
Interactive Prior Elicitation of Feature Similarities for Small Sample Size Prediction. UMAP 2017: 265-269 - [r2]Samuel Kaski:
Self-Organizing Maps. Encyclopedia of Machine Learning and Data Mining 2017: 1129-1132 - [i33]Makoto Yamada, Song Liu, Samuel Kaski:
Interpreting Outliers: Localized Logistic Regression for Density Ratio Estimation. CoRR abs/1702.06354 (2017) - [i32]Xiangju Qin, Paul Blomstedt, Eemeli Leppäaho, Pekka Parviainen, Samuel Kaski:
Distributed Bayesian Matrix Factorization with Minimal Communication. CoRR abs/1703.00734 (2017) - [i31]Mikko A. Heikkilä, Yusuke Okimoto, Samuel Kaski, Kana Shimizu, Antti Honkela:
Differentially Private Bayesian Learning on Distributed Data. CoRR abs/1703.01106 (2017) - [i30]Antti Kangasrääsiö, Samuel Kaski:
Inverse Reinforcement Learning from Summary Data. CoRR abs/1703.09700 (2017) - [i29]Iiris Sundin, Tomi Peltola, Muntasir Mamun Majumder, Pedram Daee, Marta Soare, Homayun Afrabandpey, Caroline Heckman, Samuel Kaski, Pekka Marttinen:
Improving drug sensitivity predictions in precision medicine through active expert knowledge elicitation. CoRR abs/1705.03290 (2017) - [i28]Yao Lu, Zhirong Yang, Juho Kannala, Samuel Kaski:
Learning Image Relations with Contrast Association Networks. CoRR abs/1705.05665 (2017) - [i27]Sami Remes, Markus Heinonen, Samuel Kaski:
Non-Stationary Spectral Kernels. CoRR abs/1705.08736 (2017) - [i26]Jarno Lintusaari, Henri Vuollekoski, Antti Kangasrääsiö, Kusti Skytén, Marko Järvenpää, Michael U. Gutmann, Aki Vehtari, Jukka Corander, Samuel Kaski:
ELFI: Engine for Likelihood Free Inference. CoRR abs/1708.00707 (2017) - [i25]Pedram Daee, Tomi Peltola, Aki Vehtari, Samuel Kaski:
User Modelling for Avoiding Overfitting in Interactive Knowledge Elicitation for Prediction. CoRR abs/1710.04881 (2017) - 2016
- [j71]Paul Blomstedt, Ritabrata Dutta, Sohan Seth, Alvis Brazma, Samuel Kaski:
Modelling-based experiment retrieval: a case study with gene expression clustering. Bioinform. 32(9): 1388-1394 (2016) - [j70]Kerstin Bunte, Eemeli Leppäaho, Inka Saarinen, Samuel Kaski:
Sparse group factor analysis for biclustering of multiple data sources. Bioinform. 32(16): 2457-2463 (2016) - [j69]Muhammad Ammad-ud-din, Suleiman A. Khan, Disha Malani, Astrid Murumägi, Olli-P. Kallioniemi, Tero Aittokallio, Samuel Kaski:
Drug response prediction by inferring pathway-response associations with kernelized Bayesian matrix factorization. Bioinform. 32(17): 455-463 (2016) - [j68]José Caldas, Samuel Kaski:
A Latent Feature Model Approach to Biclustering. Int. J. Knowl. Discov. Bioinform. 6(2): 11-28 (2016) - [j67]Jussi Gillberg, Pekka Marttinen, Matti Pirinen, Antti J. Kangas, Pasi Soininen, Mehreen Ali, Aki S. Havulinna, Marjo-Riitta Järvelin, Mika Ala-Korpela, Samuel Kaski:
Multiple Output Regression with Latent Noise. J. Mach. Learn. Res. 17: 122:1-122:35 (2016) - [j66]Suleiman A. Khan, Eemeli Leppäaho, Samuel Kaski:
Bayesian multi-tensor factorization. Mach. Learn. 105(2): 233-253 (2016) - [j65]Oswald Barral, Ilkka Kosunen, Tuukka Ruotsalo, Michiel M. A. Spapé, Manuel J. A. Eugster, Niklas Ravaja, Samuel Kaski, Giulio Jacucci:
Extracting relevance and affect information from physiological text annotation. User Model. User Adapt. Interact. 26(5): 493-520 (2016) - [c96]Markus Heinonen, Henrik Mannerström, Juho Rousu, Samuel Kaski, Harri Lähdesmäki:
Non-Stationary Gaussian Process Regression with Hamiltonian Monte Carlo. AISTATS 2016: 732-740 - [c95]Seppo Virtanen, Homayun Afrabandpey, Samuel Kaski:
Visualizations relevant to the user by multi-view latent variable factorization. ICASSP 2016: 2464-2468 - [c94]Marta Soare, Muhammad Ammad-ud-din, Samuel Kaski:
Regression with n→1 by Expert Knowledge Elicitation. ICMLA 2016: 734-739 - [c93]Junning Gao, Makoto Yamada, Samuel Kaski, Hiroshi Mamitsuka, Shanfeng Zhu:
A Robust Convex Formulation for Ensemble Clustering. IJCAI 2016: 1476-1482 - [c92]Hamed Rezazadegan Tavakoli, Hanieh Poostchi, Jaakko Peltonen, Jorma Laaksonen, Samuel Kaski:
Preliminary Studies on Personalized Preference Prediction from Gaze in Comparing Visualizations. ISVC (2) 2016: 576-585 - [c91]Antti Kangasrääsiö, Yi Chen, Dorota Glowacka, Samuel Kaski:
Dealing with Concept Drift in Exploratory Search: An Interactive Bayesian Approach. IUI Companion 2016: 62-66 - [c90]Pedram Daee, Joel Pyykkö, Dorota Glowacka, Samuel Kaski:
Interactive Intent Modeling from Multiple Feedback Domains. IUI 2016: 71-75 - [c89]Pekka Parviainen, Samuel Kaski:
Bayesian Networks for Variable Groups. Probabilistic Graphical Models 2016: 380-391 - [c88]Antti Kangasrääsiö, Yi Chen, Dorota Glowacka, Samuel Kaski:
Interactive Modeling of Concept Drift and Errors in Relevance Feedback. UMAP 2016: 185-193 - [i24]Sahely Bhadra, Samuel Kaski, Juho Rousu:
Multi-view Kernel Completion. CoRR abs/1602.02518 (2016) - [i23]Antti Kangasrääsiö, Yi Chen, Dorota Glowacka, Samuel Kaski:
Interactive Modeling of Concept Drift and Errors in Relevance Feedback. CoRR abs/1603.02609 (2016) - [i22]Makoto Yamada, Koh Takeuchi, Tomoharu Iwata, John Shawe-Taylor, Samuel Kaski:
Sparse Network Lasso for Local High-dimensional Regression. CoRR abs/1603.06743 (2016) - [i21]Marta Soare, Muhammad Ammad-ud-din, Samuel Kaski:
Regression with n$\to$1 by Expert Knowledge Elicitation. CoRR abs/1605.06477 (2016) - [i20]Antti Honkela, Mrinal Das, Onur Dikmen, Samuel Kaski:
Efficient differentially private learning improves drug sensitivity prediction. CoRR abs/1606.02109 (2016) - [i19]Muhammad Ammad-ud-din, Suleiman A. Khan, Disha Malani, Astrid Murumägi, Olli-P. Kallioniemi, Tero Aittokallio, Samuel Kaski:
Drug response prediction by inferring pathway-response associations with Kernelized Bayesian Matrix Factorization. CoRR abs/1606.03623 (2016) - [i18]Manuel J. A. Eugster, Tuukka Ruotsalo, Michiel M. A. Spapé, Oswald Barral, Niklas Ravaja, Giulio Jacucci, Samuel Kaski:
Natural brain-information interfaces: Recommending information by relevance inferred from human brain signals. CoRR abs/1607.03502 (2016) - [i17]Eemeli Leppäaho, Muhammad Ammad-ud-din, Samuel Kaski:
GFA: Exploratory Analysis of Multiple Data Sources with Group Factor Analysis. CoRR abs/1611.01534 (2016) - [i16]Antti Kangasrääsiö, Kumaripaba Athukorala, Andrew Howes, Jukka Corander, Samuel Kaski, Antti Oulasvirta:
Inverse Modeling of Complex Interactive Behavior with ABC. CoRR abs/1612.00653 (2016) - [i15]Luana Micallef, Iiris Sundin, Pekka Marttinen, Muhammad Ammad-ud-din, Tomi Peltola, Marta Soare, Giulio Jacucci, Samuel Kaski:
Interactive Elicitation of Knowledge on Feature Relevance Improves Predictions in Small Data Sets. CoRR abs/1612.02487 (2016) - [i14]Homayun Afrabandpey, Tomi Peltola, Samuel Kaski:
Interactive Prior Elicitation of Features Similarities for Small Sample Size Prediction. CoRR abs/1612.02802 (2016) - [i13]Pedram Daee, Tomi Peltola, Marta Soare, Samuel Kaski:
Knowledge Elicitation via Sequential Probabilistic Inference for High-Dimensional Prediction. CoRR abs/1612.03328 (2016) - 2015
- [j64]Tuukka Ruotsalo, Giulio Jacucci, Petri Myllymäki, Samuel Kaski:
Interactive intent modeling: information discovery beyond search. Commun. ACM 58(1): 86-92 (2015) - [j63]Jukka-Pekka Kauppi, Melih Kandemir, Veli-Matti Saarinen, Lotta Hirvenkari, Lauri Parkkonen, Arto Klami, Riitta Hari, Samuel Kaski:
Towards brain-activity-controlled information retrieval: Decoding image relevance from MEG signals. NeuroImage 112: 288-298 (2015) - [j62]Arto Klami, Seppo Virtanen, Eemeli Leppäaho, Samuel Kaski:
Group Factor Analysis. IEEE Trans. Neural Networks Learn. Syst. 26(9): 2136-2147 (2015) - [c87]Zhirong Yang, Jaakko Peltonen, Samuel Kaski:
Majorization-Minimization for Manifold Embedding. AISTATS 2015 - [c86]Antti Kangasrääsiö, Dorota Glowacka, Samuel Kaski:
Improving Controllability and Predictability of Interactive Recommendation Interfaces for Exploratory Search. IUI 2015: 247-251 - [c85]Oswald Barral, Manuel J. A. Eugster, Tuukka Ruotsalo, Michiel M. A. Spapé, Ilkka Kosunen, Niklas Ravaja, Samuel Kaski, Giulio Jacucci:
Exploring Peripheral Physiology as a Predictor of Perceived Relevance in Information Retrieval. IUI 2015: 389-399 - [c84]Tuukka Ruotsalo, Jaakko Peltonen, Manuel J. A. Eugster, Dorota Glowacka, Aki Reijonen, Giulio Jacucci, Petri Myllymäki, Samuel Kaski:
SciNet: Interactive Intent Modeling for Information Discovery. SIGIR 2015: 1043-1044 - [c83]Luciano Gamberini, Anna Spagnolli, Benjamin Blankertz, Samuel Kaski, Jonathan Freeman, Laura Acqualagna, Oswald Barral, Maura Bellio, Luca Chech, Manuel J. A. Eugster, Eva Ferrari, Paolo Negri, Valeria Orso, Patrik Pluchino, Filippo Minelle, Baris Serim, Markus A. Wenzel, Giulio Jacucci:
Developing a Symbiotic System for Scientific Information Seeking: The MindSee Project. Symbiotic 2015: 68-80 - [i12]Paul Blomstedt, Ritabrata Dutta, Sohan Seth, Alvis Brazma, Samuel Kaski:
Modelling-based experiment retrieval: A case study with gene expression clustering. CoRR abs/1505.05007 (2015) - [i11]Pekka Parviainen, Samuel Kaski:
Bayesian Networks for Variable Groups. CoRR abs/1508.07753 (2015) - [i10]Seppo Virtanen, Homayun Afrabandpey, Samuel Kaski:
Visualizations Relevant to The User By Multi-View Latent Variable Factorization. CoRR abs/1512.07807 (2015) - [i9]Kerstin Bunte, Eemeli Leppäaho, Inka Saarinen, Samuel Kaski:
Sparse group factor analysis for biclustering of multiple data sources. CoRR abs/1512.08808 (2015) - 2014
- [j61]Pekka Marttinen, Matti Pirinen, Antti-Pekka Sarin, Jussi Gillberg, Johannes Kettunen, Ida Surakka, Antti J. Kangas, Pasi Soininen, Paul F. O'Reilly, Marika Kaakinen, Mika Kähönen, Terho Lehtimäki, Mika Ala-Korpela, Olli T. Raitakari, Veikko Salomaa, Marjo-Riitta Järvelin, Samuli Ripatti, Samuel Kaski:
Assessing multivariate gene-metabolome associations with rare variants using Bayesian reduced rank regression. Bioinform. 30(14): 2026-2034 (2014) - [j60]Tommi Suvitaival, Simon Rogers, Samuel Kaski:
Stronger findings for metabolomics through Bayesian modeling of multiple peaks and compound correlations. Bioinform. 30(17): 461-467 (2014) - [j59]Suleiman A. Khan, Seppo Virtanen, Olli-P. Kallioniemi, Krister Wennerberg, Antti Poso, Samuel Kaski:
Identification of structural features in chemicals associated with cancer drug response: a systematic data-driven analysis. Bioinform. 30(17): 497-504 (2014) - [j58]Sohan Seth, Niko Välimäki, Samuel Kaski, Antti Honkela:
Exploration and retrieval of whole-metagenome sequencing samples. Bioinform. 30(17): 2471-2479 (2014) - [j57]Juuso A. Parkkinen, Samuel Kaski:
Probabilistic drug connectivity mapping. BMC Bioinform. 15: 113 (2014) - [j56]Tommi Suvitaival, Simon Rogers, Samuel Kaski:
Stronger findings from mass spectral data through multi-peak modeling. BMC Bioinform. 15: 208 (2014) - [j55]Melih Kandemir, Akos Vetek, Mehmet Gönen, Arto Klami, Samuel Kaski:
Multi-task and multi-view learning of user state. Neurocomputing 139: 97-106 (2014) - [j54]Muhammad Ammad-ud-din, Elisabeth Georgii, Mehmet Gönen, Tuomo Laitinen, Olli-P. Kallioniemi, Krister Wennerberg, Antti Poso, Samuel Kaski:
Integrative and Personalized QSAR Analysis in Cancer by Kernelized Bayesian Matrix Factorization. J. Chem. Inf. Model. 54(8): 2347-2359 (2014) - [j53]Mehmet Gönen, Samuel Kaski:
Kernelized Bayesian Matrix Factorization. IEEE Trans. Pattern Anal. Mach. Intell. 36(10): 2047-2060 (2014) - [c82]Kerstin Bunte, Matti Järvisalo, Jeremias Berg, Petri Myllymäki, Jaakko Peltonen, Samuel Kaski:
Optimal Neighborhood Preserving Visualization by Maximum Satisfiability. AAAI 2014: 1694-1700 - [c81]Samuel Kaski, Jukka Corander:
Preface. AISTATS 2014: i-iv - [c80]Tuukka Ruotsalo, Jaakko Peltonen, Manuel J. A. Eugster, Dorota Glowacka, Aki Reijonen, Giulio Jacucci, Petri Myllymäki, Samuel Kaski:
Intentradar: search user interface that anticipates user's search intents. CHI Extended Abstracts 2014: 455-458 - [c79]Zhirong Yang, Jaakko Peltonen, Samuel Kaski:
Optimization Equivalence of Divergences Improves Neighbor Embedding. ICML 2014: 460-468 - [c78]Sohan Seth, John Shawe-Taylor, Samuel Kaski:
Retrieval of Experiments by Efficient Comparison of Marginal Likelihoods. ICONIP (2) 2014: 135-142 - [c77]Suleiman A. Khan, Samuel Kaski:
Bayesian Multi-view Tensor Factorization. ECML/PKDD (1) 2014: 656-671 - [c76]Manuel J. A. Eugster, Tuukka Ruotsalo, Michiel M. A. Spapé, Ilkka Kosunen, Oswald Barral, Niklas Ravaja, Giulio Jacucci, Samuel Kaski:
Predicting term-relevance from brain signals. SIGIR 2014: 425-434 - [i8]Sohan Seth, John Shawe-Taylor, Samuel Kaski:
Retrieval of Experiments by Efficient Estimation of Marginal Likelihood. CoRR abs/1402.4653 (2014) - [i7]Zakria Hussain, Arto Klami, Jussi Kujala, Alex Po Leung, Kitsuchart Pasupa, Peter Auer, Samuel Kaski, Jorma Laaksonen, John Shawe-Taylor:
PinView: Implicit Feedback in Content-Based Image Retrieval. CoRR abs/1410.0471 (2014) - 2013
- [j52]Arto Klami, Seppo Virtanen, Samuel Kaski:
Bayesian Canonical correlation analysis. J. Mach. Learn. Res. 14(1): 965-1003 (2013) - [c75]Tuukka Ruotsalo, Kumaripaba Athukorala, Dorota Glowacka, Ksenia Konyushkova, Antti Oulasvirta, Samuli Kaipiainen, Samuel Kaski, Giulio Jacucci:
Supporting exploratory search tasks with interactive user modeling. ASIST 2013: 1-10 - [c74]Tuukka Ruotsalo, Jaakko Peltonen, Manuel J. A. Eugster, Dorota Glowacka, Ksenia Konyushkova, Kumaripaba Athukorala, Ilkka Kosunen, Aki Reijonen, Petri Myllymäki, Giulio Jacucci, Samuel Kaski:
Directing exploratory search with interactive intent modeling. CIKM 2013: 1759-1764 - [c73]Antti Ajanki, Markus Koskela, Jorma Laaksonen, Samuel Kaski:
Adaptive timeline interface to personal history data. ICMI 2013: 229-236 - [c72]Zhirong Yang, Jaakko Peltonen, Samuel Kaski:
Scalable Optimization of Neighbor Embedding for Visualization. ICML (2) 2013: 127-135 - [c71]Mehmet Gönen, Suleiman A. Khan, Samuel Kaski:
Kernelized Bayesian Matrix Factorization. ICML (3) 2013: 864-872 - [c70]Dorota Glowacka, Tuukka Ruotsalo, Ksenia Konyushkova, Kumaripaba Athukorala, Samuel Kaski, Giulio Jacucci:
SciNet: a system for browsing scientific literature through keyword manipulation. IUI Companion 2013: 61-62 - [c69]Dorota Glowacka, Tuukka Ruotsalo, Ksenia Konyushkova, Kumaripaba Athukorala, Samuel Kaski, Giulio Jacucci:
Directing exploratory search: reinforcement learning from user interactions with keywords. IUI 2013: 117-128 - [c68]Jaakko Peltonen, Max Sandholm, Samuel Kaski:
Information Retrieval Perspective to Interactive Data Visualization. EuroVis (Short Papers) 2013 - [i6]Sohan Seth, Niko Välimäki, Samuel Kaski, Antti Honkela:
Exploration and retrieval of whole-metagenome sequencing samples. CoRR abs/1308.6074 (2013) - [i5]Ritabrata Dutta, Sohan Seth, Samuel Kaski:
Retrieval of Experiments with Sequential Dirichlet Process Mixtures in Model Space. CoRR abs/1310.2125 (2013) - [i4]Jussi Gillberg, Pekka Marttinen, Matti Pirinen, Antti J. Kangas, Pasi Soininen, Marjo-Riitta Järvelin, Mika Ala-Korpela, Samuel Kaski:
Bayesian Information Sharing Between Noise And Regression Models Improves Prediction of Weak Effects. CoRR abs/1310.4362 (2013) - 2012
- [j51]José Caldas, Nils Gehlenborg, Eeva Kettunen, Ali Faisal, Mikko Rönty, Andrew G. Nicholson, Sakari Knuutila, Alvis Brazma, Samuel Kaski:
Data-driven information retrieval in heterogeneous collections of transcriptomics data links SIM2s to malignant pleural mesothelioma. Bioinform. 28(2): 246-253 (2012) - [j50]Elisabeth Georgii, Jarkko Salojärvi, Mikael Brosché, Jaakko Kangasjärvi, Samuel Kaski:
Targeted retrieval of gene expression measurements using regulatory models. Bioinform. 28(18): 2349-2356 (2012) - [j49]Suleiman A. Khan, Ali Faisal, John Mpindi, Juuso A. Parkkinen, Tuomo Kalliokoski, Antti Poso, Olli-P. Kallioniemi, Krister Wennerberg, Samuel Kaski:
Comprehensive data-driven analysis of the impact of chemoinformatic structure on the genome-wide biological response profiles of cancer cells to 1159 drugs. BMC Bioinform. 13: 112 (2012) - [j48]Jaakko Peltonen, Tapani Raiko, Samuel Kaski:
Machine learning for signal processing 2010. Neurocomputing 80: 1-2 (2012) - [j47]Gayle Leen, Jaakko Peltonen, Samuel Kaski:
Focused multi-task learning in a Gaussian process framework. Mach. Learn. 89(1-2): 157-182 (2012) - [c67]Ali Faisal, Jussi Gillberg, Jaakko Peltonen, Gayle Leen, Samuel Kaski:
Sparse Nonparametric Topic Model for Transfer Learning. ESANN 2012 - [c66]Melih Kandemir, Samuel Kaski:
Learning relevance from natural eye movements in pervasive interfaces. ICMI 2012: 85-92 - [c65]Melih Kandemir, Arto Klami, Akos Vetek, Samuel Kaski:
Unsupervised Inference of Auditory Attention from Biosensors. ECML/PKDD (2) 2012: 403-418 - [c64]Seppo Virtanen, Arto Klami, Suleiman A. Khan, Samuel Kaski:
Bayesian Group Factor Analysis. AISTATS 2012: 1269-1277 - [i3]Leo Lahti, Juha E. A. Knuuttila, Samuel Kaski:
Global modeling of transcriptional responses in interaction networks. CoRR abs/1202.0501 (2012) - [i2]Arto Klami, Seppo Virtanen, Samuel Kaski:
Bayesian exponential family projections for coupled data sources. CoRR abs/1203.3489 (2012) - [i1]Eerika Savia, Kai Puolamäki, Janne Sinkkonen, Samuel Kaski:
Two-Way Latent Grouping Model for User Preference Prediction. CoRR abs/1207.1414 (2012) - 2011
- [j46]Abhishek Tripathi, Arto Klami, Matej Oresic, Samuel Kaski:
Matching samples of multiple views. Data Min. Knowl. Discov. 23(2): 300-321 (2011) - [j45]José Caldas, Samuel Kaski:
Hierarchical Generative Biclustering for MicroRNA Expression Analysis. J. Comput. Biol. 18(3): 251-261 (2011) - [j44]S. V. N. Vishwanathan, Samuel Kaski, Jennifer Neville, Stefan Wrobel:
Introduction to the special issue on mining and learning with graphs. Mach. Learn. 82(2): 91-93 (2011) - [j43]Marko Sysi-Aho, Andrey Ermolov, Peddinti V. Gopalacharyulu, Abhishek Tripathi, Tuulikki Seppänen-Laakso, Johanna Maukonen, Ismo Mattila, Suvi T. Ruohonen, Laura Vähätalo, Laxman Yetukuri, Taina Härkönen, Erno Lindfors, Janne Nikkilä, Jorma Ilonen, Olli Simell, Maria Saarela, Mikael Knip, Samuel Kaski, Eriika Savontaus, Matej Oresic:
Metabolic Regulation in Progression to Autoimmune Diabetes. PLoS Comput. Biol. 7(10) (2011) - [j42]Samuel Kaski, Jaakko Peltonen:
Dimensionality Reduction for Data Visualization [Applications Corner]. IEEE Signal Process. Mag. 28(2): 100-104 (2011) - [j41]Leo Lahti, Laura Elo, Tero Aittokallio, Samuel Kaski:
Probabilistic Analysis of Probe Reliability in Differential Gene Expression Studies with Short Oligonucleotide Arrays. IEEE ACM Trans. Comput. Biol. Bioinform. 8(1): 217-225 (2011) - [j40]Antti Ajanki, Mark Billinghurst, Hannes Gamper, Toni Järvenpää, Melih Kandemir, Samuel Kaski, Markus Koskela, Mikko Kurimo, Jorma Laaksonen, Kai Puolamäki, Teemu Ruokolainen, Timo Tossavainen:
An augmented reality interface to contextual information. Virtual Real. 15(2-3): 161-173 (2011) - [c63]Tommi Suvitaival, Ilkka Huopaniemi, Matej Oresic, Samuel Kaski:
Cross-Species Translation of Multi-way Biomarkers. ICANN (1) 2011: 209-216 - [c62]Antti Ajanki, Samuel Kaski:
Probabilistic Proactive Timeline Browser. ICANN (2) 2011: 357-364 - [c61]Seppo Virtanen, Arto Klami, Samuel Kaski:
Bayesian CCA via Group Sparsity. ICML 2011: 457-464 - [c60]Mehmet Gönen, Melih Kandemir, Samuel Kaski:
Multitask Learning Using Regularized Multiple Kernel Learning. ICONIP (2) 2011: 500-509 - [c59]Gayle Leen, Jaakko Peltonen, Samuel Kaski:
Focused Multi-task Learning Using Gaussian Processes. ECML/PKDD (2) 2011: 310-325 - [c58]Jaakko Peltonen, Samuel Kaski:
Generative Modeling for Maximizing Precision and Recall in Information Visualization. AISTATS 2011: 579-587 - [e2]Timo Honkela, Wlodzislaw Duch, Mark A. Girolami, Samuel Kaski:
Artificial Neural Networks and Machine Learning - ICANN 2011 - 21st International Conference on Artificial Neural Networks, Espoo, Finland, June 14-17, 2011, Proceedings, Part I. Lecture Notes in Computer Science 6791, Springer 2011, ISBN 978-3-642-21734-0 [contents] - [e1]Timo Honkela, Wlodzislaw Duch, Mark A. Girolami, Samuel Kaski:
Artificial Neural Networks and Machine Learning - ICANN 2011 - 21st International Conference on Artificial Neural Networks, Espoo, Finland, June 14-17, 2011, Proceedings, Part II. Lecture Notes in Computer Science 6792, Springer 2011, ISBN 978-3-642-21737-1 [contents] - 2010
- [j39]Ilkka Huopaniemi, Tommi Suvitaival, Janne Nikkilä, Matej Oresic, Samuel Kaski:
Multivariate multi-way analysis of multi-source data. Bioinform. 26(12): 391-398 (2010) - [j38]Leo Lahti, Juha E. A. Knuuttila, Samuel Kaski:
Global modeling of transcriptional responses in interaction networks. Bioinform. 26(21): 2713-2720 (2010) - [j37]Juuso A. Parkkinen, Samuel Kaski:
Searching for functional gene modules with interaction component models. BMC Syst. Biol. 4: 4 (2010) - [j36]Jaakko Peltonen, Yusuf Yaslan, Samuel Kaski:
Relevant subtask learning by constrained mixture models. Intell. Data Anal. 14(6): 641-662 (2010) - [j35]Jarkko Venna, Jaakko Peltonen, Kristian Nybo, Helena Aidos, Samuel Kaski:
Information Retrieval Perspective to Nonlinear Dimensionality Reduction for Data Visualization. J. Mach. Learn. Res. 11: 451-490 (2010) - [j34]Simon Rogers, Arto Klami, Janne Sinkkonen, Mark A. Girolami, Samuel Kaski:
Infinite factorization of multiple non-parametric views. Mach. Learn. 79(1-2): 201-226 (2010) - [c57]Melih Kandemir, Veli-Matti Saarinen, Samuel Kaski:
Inferring object relevance from gaze in dynamic scenes. ETRA 2010: 105-108 - [c56]Jaakko Peltonen, Helena Aidos, Nils Gehlenborg, Alvis Brazma, Samuel Kaski:
An information retrieval perspective on visualization of gene expression data with ontological annotation. ICASSP 2010: 2178-2181 - [c55]Juuso A. Parkkinen, Kristian Nybo, Jaakko Peltonen, Samuel Kaski:
Graph visualization with latent variable models. MLG@KDD 2010: 94-101 - [c54]Jaakko Viinikanoja, Arto Klami, Samuel Kaski:
Variational Bayesian Mixture of Robust CCA Models. ECML/PKDD (3) 2010: 370-385 - [c53]Ilkka Huopaniemi, Tommi Suvitaival, Matej Oresic, Samuel Kaski:
Graphical Multi-way Models. ECML/PKDD (1) 2010: 538-553 - [c52]José Caldas, Samuel Kaski:
Hierarchical Generative Biclustering for MicroRNA Expression Analysis. RECOMB 2010: 65-79 - [c51]Arto Klami, Seppo Virtanen, Samuel Kaski:
Bayesian exponential family projections for coupled data sources. UAI 2010: 286-293 - [c50]Peter Auer, Zakria Hussain, Samuel Kaski, Arto Klami, Jussi Kujala, Jorma Laaksonen, Alex Po Leung, Kitsuchart Pasupa, John Shawe-Taylor:
Pinview: Implicit Feedback in Content-Based Image Retrieval. WAPA 2010: 51-57 - [p2]Samuel Kaski:
Three Paths to Relevance. Brain-Inspired Information Technology 2010: 11-13 - [r1]Samuel Kaski:
Self-Organizing Maps. Encyclopedia of Machine Learning 2010: 886-888
2000 – 2009
- 2009
- [j33]José Caldas, Nils Gehlenborg, Ali Faisal, Alvis Brazma, Samuel Kaski:
Probabilistic retrieval and visualization of biologically relevant microarray experiments. Bioinform. 25(12) (2009) - [j32]José Caldas, Nils Gehlenborg, Ali Faisal, Alvis Brazma, Samuel Kaski:
Probabilistic retrieval and visualization of biologically relevant microarray experiments. BMC Bioinform. 10(S-13): 0 (2009) - [j31]Jaakko Peltonen, Jarkko Venna, Samuel Kaski:
Visualizations for assessing convergence and mixing of Markov chain Monte Carlo simulations. Comput. Stat. Data Anal. 53(12): 4453-4470 (2009) - [j30]Ilkka Huopaniemi, Tommi Suvitaival, Janne Nikkilä, Matej Oresic, Samuel Kaski:
Two-way analysis of high-dimensional collinear data. Data Min. Knowl. Discov. 19(2): 261-276 (2009) - [j29]Eerika Savia, Kai Puolamäki, Samuel Kaski:
Latent grouping models for user preference prediction. Mach. Learn. 74(1): 75-109 (2009) - [j28]Jarkko Ylipaavalniemi, Eerika Savia, Sanna Malinen, Riitta Hari, Ricardo Vigário, Samuel Kaski:
Dependencies between stimuli and spatially independent fMRI sources: Towards brain correlates of natural stimuli. NeuroImage 48(1): 176-185 (2009) - [j27]Antti Ajanki, David R. Hardoon, Samuel Kaski, Kai Puolamäki, John Shawe-Taylor:
Can eyes reveal interest? Implicit queries from gaze patterns. User Model. User Adapt. Interact. 19(4): 307-339 (2009) - [c49]Gayle Leen, David R. Hardoon, Samuel Kaski:
Automatic Choice of Control Measurements. ACML 2009: 206-219 - [c48]Abhishek Tripathi, Arto Klami, Samuel Kaski:
Using dependencies to pair samples for multi-view learning. ICASSP 2009: 1561-1564 - [c47]Eerika Savia, Arto Klami, Samuel Kaski:
Fast dependent components for fMRI analysis. ICASSP 2009: 1737-1740 - [c46]Jaakko Peltonen, Helena Aidos, Samuel Kaski:
Supervised nonlinear dimensionality reduction by Neighbor Retrieval. ICASSP 2009: 1809-1812 - [c45]Kitsuchart Pasupa, Craig Saunders, Sándor Szedmák, Arto Klami, Samuel Kaski, Steve R. Gunn:
Learning to rank images from eye movements. ICCV Workshops 2009: 2009-2016 - [c44]László Kozma, Arto Klami, Samuel Kaski:
GaZIR: gaze-based zooming interface for image retrieval. ICMI 2009: 305-312 - [c43]Eerika Savia, Kai Puolamäki, Samuel Kaski:
Two-Way Grouping by One-Way Topic Models. IDA 2009: 178-189 - [c42]Kai Puolamäki, Samuel Kaski:
Bayesian Solutions to the Label Switching Problem. IDA 2009: 381-392 - [c41]Ilkka Huopaniemi, Tommi Suvitaival, Janne Nikkilä, Matej Oresic, Samuel Kaski:
Two-Way Analysis of High-Dimensional Collinear Data. ECML/PKDD (1) 2009: 33 - 2008
- [j26]Abhishek Tripathi, Arto Klami, Samuel Kaski:
Simple integrative preprocessing preserves what is shared in data sources. BMC Bioinform. 9 (2008) - [j25]Arto Klami, Samuel Kaski:
Probabilistic approach to detecting dependencies between data sets. Neurocomputing 72(1-3): 39-46 (2008) - [c40]Kai Puolamäki, Antti Ajanki, Samuel Kaski:
Learning to learn implicit queries from gaze patterns. ICML 2008: 760-767 - [c39]Keisuke Yamazaki, Samuel Kaski:
An Analysis of Generalization Error in Relevant Subtask Learning. ICONIP (1) 2008: 629-637 - [c38]Arto Klami, Craig Saunders, Teófilo Emídio de Campos, Samuel Kaski:
Can relevance of images be inferred from eye movements? Multimedia Information Retrieval 2008: 134-140 - 2007
- [j24]Samuel Kaski, Juho Rousu, Esko Ukkonen:
Probabilistic modeling and machine learning in structural and systems biology. BMC Bioinform. 8(S-2) (2007) - [j23]Merja Oja, Jaakko Peltonen, Jonas Blomberg, Samuel Kaski:
Methods for estimating human endogenous retrovirus activities from EST databases. BMC Bioinform. 8(S-2) (2007) - [j22]Jarkko Venna, Samuel Kaski:
Comparison of visualization methods for an atlas of gene expression data sets. Inf. Vis. 6(2): 139-154 (2007) - [c37]Samuel Kaski, Jaakko Peltonen:
Learning from Relevant Tasks Only. ECML 2007: 608-615 - [c36]Jarkko Ylipaavalniemi, Eerika Savia, Ricardo Vigário, Samuel Kaski:
Functional elements and networks in fMRI. ESANN 2007: 561-566 - [c35]Arto Klami, Samuel Kaski:
Local dependent components. ICML 2007: 425-432 - [c34]Janne Sinkkonen, Janne Aukia, Samuel Kaski:
Inferring Vertex Properties from Topology in Large Networks. MLG 2007 - [c33]David R. Hardoon, John Shawe-Taylor, Antti Ajanki, Kai Puolamäki, Samuel Kaski:
Information Retrieval by Inferring Implicit Queries from Eye Movements. AISTATS 2007: 179-186 - [c32]Jarkko Venna, Samuel Kaski:
Nonlinear Dimensionality Reduction as Information Retrieval. AISTATS 2007: 572-579 - 2006
- [j21]Jarkko Venna, Samuel Kaski:
Local multidimensional scaling. Neural Networks 19(6-7): 889-899 (2006) - [c31]Udo Seiffert, Barbara Hammer, Samuel Kaski, Thomas Villmann:
Neural networks and machine learning in bioinformatics - theory and applications. ESANN 2006: 521-532 - [c30]Jarkko Venna, Samuel Kaski:
Visualizing gene interaction graphs with local multidimensional scaling. ESANN 2006: 557-562 - 2005
- [j20]Merja Oja, Göran O. Sperber, Jonas Blomberg, Samuel Kaski:
Self-organizing map-based discovery and visualization of human endogenous retroviral sequence groups. Int. J. Neural Syst. 15(3): 163-179 (2005) - [j19]Janne Nikkilä, Christophe Roos, Eerika Savia, Samuel Kaski:
Exploratory modeling of yeast stress response and its regulation with gcca and associative clustering. Int. J. Neural Syst. 15(4): 237-246 (2005) - [j18]Samuel Kaski, Janne Sinkkonen, Arto Klami:
Discriminative clustering. Neurocomputing 69(1-3): 18-41 (2005) - [j17]Samuel Kaski, Janne Nikkilä, Janne Sinkkonen, Leo Lahti, Juha E. A. Knuuttila, Christophe Roos:
Associative Clustering for Exploring Dependencies between Functional Genomics Data Sets. IEEE ACM Trans. Comput. Biol. Bioinform. 2(3): 203-216 (2005) - [j16]Jaakko Peltonen, Samuel Kaski:
Discriminative components of data. IEEE Trans. Neural Networks 16(1): 68-83 (2005) - [c29]Jarkko Salojärvi, Kai Puolamäki, Samuel Kaski:
On Discriminative Joint Density Modeling. ECML 2005: 341-352 - [c28]Jarkko Salojärvi, Kai Puolamäki, Samuel Kaski:
Implicit Relevance Feedback from Eye Movements. ICANN (1) 2005: 513-518 - [c27]Arto Klami, Samuel Kaski:
Non-parametric dependent components. ICASSP (5) 2005: 209-212 - [c26]Jarkko Salojärvi, Kai Puolamäki, Samuel Kaski:
Expectation maximization algorithms for conditional likelihoods. ICML 2005: 752-759 - [c25]Kai Puolamäki, Jarkko Salojärvi, Eerika Savia, Jaana Simola, Samuel Kaski:
Combining eye movements and collaborative filtering for proactive information retrieval. SIGIR 2005: 146-153 - [c24]Eerika Savia, Kai Puolamäki, Janne Sinkkonen, Samuel Kaski:
Two-Way Latent Grouping Model for User Preference Prediction. UAI 2005: 518-524 - 2004
- [j15]Krista Lagus, Samuel Kaski, Teuvo Kohonen:
Mining massive document collections by the WEBSOM method. Inf. Sci. 163(1-3): 135-156 (2004) - [j14]Jaakko Peltonen, Arto Klami, Samuel Kaski:
Improved learning of Riemannian metrics for exploratory analysis. Neural Networks 17(8-9): 1087-1100 (2004) - [j13]Samuel Kaski, Janne Sinkkonen:
Principle of Learning Metrics for Exploratory Data Analysis. J. VLSI Signal Process. 37(2-3): 177-188 (2004) - [c23]Merja Oja, Göran O. Sperber, Jonas Blomberg, Samuel Kaski:
Grouping and visualizing human endogenous retroviruses by bootstrapping median self-organizing maps. CIBCB 2004: 95-101 - [c22]Janne Sinkkonen, Janne Nikkilä, Leo Lahti, Samuel Kaski:
Associative Clustering. ECML 2004: 396-406 - [c21]Jaakko Peltonen, Janne Sinkkonen, Samuel Kaski:
Sequential information bottleneck for finite data. ICML 2004 - [c20]Janne Nikkilä, Christophe Roos, Samuel Kaski:
Exploring Dependencies Between Yeast Stress Genes and Their Regulators. IDEAL 2004: 92-98 - 2003
- [j12]Samuel Kaski, Janne Nikkilä, Merja Oja, Jarkko Venna, Petri Törönen, Eero Castrén:
Trustworthiness and metrics in visualizing similarity of gene expression. BMC Bioinform. 4: 48 (2003) - [c19]Jarkko Venna, Samuel Kaski, Jaakko Peltonen:
Visualizations for Assessing Convergence and Mixing of MCMC. ECML 2003: 432-443 - [c18]Samuel Kaski, Jaakko Peltonen:
Informative Discriminant Analysis. ICML 2003: 329-336 - [c17]Samuel Kaski, Janne Sinkkonen, Arto Klami:
Regularized discriminative clustering. NNSP 2003: 289-298 - [p1]Samuel Kaski, Janne Nikkilä, Teuvo Kohonen:
Methods for Exploratory Cluster Analysis. Intelligent Exploration of the Web 2003: 136-151 - 2002
- [j11]Ville Ollikainen, Christer Bäckström, Samuel Kaski:
Electronic editor: automatic content-based sequential compilation of newspaper articles. Neurocomputing 43(1-4): 91-106 (2002) - [j10]Janne Sinkkonen, Samuel Kaski:
Clustering Based on Conditional Distributions in an Auxiliary Space. Neural Comput. 14(1): 217-239 (2002) - [j9]Janne Nikkilä, Petri Törönen, Samuel Kaski, Jarkko Venna, Eero Castrén, Garry Wong:
Analysis and visualization of gene expression data using Self-Organizing Maps. Neural Networks 15(8-9): 953-966 (2002) - [c16]Janne Sinkkonen, Samuel Kaski, Janne Nikkilä:
Discriminative Clustering: Optimal Contingency Tables by Learning Metrics. ECML 2002: 418-430 - [c15]Jaakko Peltonen, Arto Klami, Samuel Kaski:
Learning More Accurate Metrics for Self-Organizing Maps. ICANN 2002: 999-1004 - 2001
- [j8]Samuel Kaski, Janne Sinkkonen, Jaakko Peltonen:
Bankruptcy analysis with self-organizing maps in learning metrics. IEEE Trans. Neural Networks 12(4): 936-947 (2001) - [c14]Samuel Kaski, Janne Sinkkonen, Jaakko Peltonen:
Data Visualization and Analysis with Self-Organizing Maps in Learning Metrics. DaWaK 2001: 162-173 - [c13]Samuel Kaski, Janne Sinkkonen, Janne Nikkilä:
Clustering Gene Expression Data by Mutual Information with Gene Function. ICANN 2001: 81-86 - [c12]Jarkko Venna, Samuel Kaski:
Neighborhood Preservation in Nonlinear Projection Methods: An Experimental Study. ICANN 2001: 485-491 - [c11]Samuel Kaski:
SOM-Based Exploratory Analysis of Gene Expression Data. WSOM 2001: 124-131 - [c10]Samuel Kaski, Janne Sinkkonen:
A Topography-Preserving Latent Variable Model with Learning Metrics. WSOM 2001: 224-229 - 2000
- [j7]Teuvo Kohonen, Samuel Kaski, Krista Lagus, Jarkko Salojärvi, Jukka Honkela, Vesa Paatero, Antti Saarela:
Self organization of a massive document collection. IEEE Trans. Neural Networks Learn. Syst. 11(3): 574-585 (2000) - [c9]Janne Sinkkonen, Samuel Kaski:
Clustering by Similarity in an Auxiliary Space. IDEAL 2000: 3-8 - [c8]Samuel Kaski, Janne Sinkkonen:
Metrics that Learn Relevance. IJCNN (5) 2000: 547-552
1990 – 1999
- 1999
- [j6]Krista Lagus, Timo Honkela, Samuel Kaski, Teuvo Kohonen:
Websom for Textual Data Mining. Artif. Intell. Rev. 13(5-6): 345-364 (1999) - 1998
- [j5]Samuel Kaski, Timo Honkela, Krista Lagus, Teuvo Kohonen:
WEBSOM - Self-organizing maps of document collections. Neurocomputing 21(1-3): 101-117 (1998) - [c7]Samuel Kaski, Janne Nikkilä, Teuvo Kohonen:
Methods for interpreting a self-organized map in data analysis. ESANN 1998: 185-190 - 1997
- [j4]Teuvo Kohonen, Samuel Kaski, Harri Lappalainen:
Self-organized Formation of Various Invariant-feature Filters in the Adaptive-subspace SOM. Neural Comput. 9(6): 1321-1344 (1997) - [j3]Samuel Kaski:
Computationally Efficient Approximation of a Probabilistic Model for Document Representation in the WEBSOM Full-Text Analysis Method. Neural Process. Lett. 5(2): 69-81 (1997) - 1996
- [c6]Teuvo Kohonen, Samuel Kaski, Krista Lagus, Timo Honkela:
Very Large Two-Level SOM for the Browsing of Newsgroups. ICANN 1996: 269-274 - [c5]Samuel Kaski, Krista Lagus:
Comparing Self-Organizing Maps. ICANN 1996: 809-814 - [c4]Jari Kangas, Samuel Kaski:
Compression of vector quantization code sequences based on code frequencies and spatial redundancies. ICIP (3) 1996: 463-466 - [c3]Timo Honkela, Samuel Kaski, Krista Lagus, Teuvo Kohonen:
Exploration of full-text databases with self-organizing maps. ICNN 1996: 56-61 - [c2]Krista Lagus, Timo Honkela, Samuel Kaski, Teuvo Kohonen:
Self-Organizing Maps of Document Collections: A New Approach to Interactive Exploration. KDD 1996: 238-243 - 1995
- [j2]Sirkka-Liisa Joutsiniemi, Samuel Kaski, T. Andreo Larsen:
Self-organizing map in recognition of topographic patterns of EEG spectra. IEEE Trans. Biomed. Eng. 42(11): 1062-1068 (1995) - 1994
- [j1]Samuel Kaski, Teuvo Kohonen:
Winner-take-all networks for physiological models of competitive learning. Neural Networks 7(6-7): 973-984 (1994) - 1992
- [c1]Pekka Utela, Samuel Kaski, Kari Torkkola:
Using phoneme group specific LVQ-codebooks with HMMs. ICSLP 1992: 551-554
Coauthor Index
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