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ORCIDPavel Kordík
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2020 – today
- 2024
[c45]Vojtech Vancura
, Pavel Kordík, Milan Straka:
beeFormer: Bridging the Gap Between Semantic and Interaction Similarity in Recommender Systems. RecSys 2024: 1102-1107- [i6]Vojtech Vancura, Pavel Kordík, Milan Straka:
beeFormer: Bridging the Gap Between Semantic and Interaction Similarity in Recommender Systems. CoRR abs/2409.10309 (2024) - 2023
- [c44]Stanislav Kuznetsov, Pavel Kordík:
Overcoming the Cold-Start Problem in Recommendation Systems with Ontologies and Knowledge Graphs. ADBIS (Short Papers) 2023: 591-603 - [c43]Cenek Zid, Pavel Kordík, Stanislav Kuznetsov:
Personalised Recommendations and Profile Based Re-ranking Improve Distribution of Student Opportunities. CISIS-ICEUTE 2023: 217-227 - [c42]Alexander Kovalenko, Pavel Kordík:
Decorelated Weight Initialization by Backpropagation. ICANN (1) 2023: 546-550 - [c41]Petr Kasalický, Rodrigo Alves, Pavel Kordík:
Bridging Offline-Online Evaluation with a Time-dependent and Popularity Bias-free Offline Metric for Recommenders. EvalRS@KDD 2023 - [i5]Petr Kasalický, Rodrigo Alves, Pavel Kordík:
Bridging Offline-Online Evaluation with a Time-dependent and Popularity Bias-free Offline Metric for Recommenders. CoRR abs/2308.06885 (2023) - 2022
- [c40]Vojtech Cahlík, Pavel Kordík, Miroslav Cepek:
Adapting the Size of Artificial Neural Networks Using Dynamic Auto-Sizing. CSIT 2022: 592-596 - [c39]Daniil Pastukhov, Stanislav Kuznetsov, Vojtech Vancura, Pavel Kordík:
Offline evaluation of the serendipity in recommendation systems. CSIT 2022: 597-601 - [c38]Jan Motl, Pavel Kordík:
Discriminant Analysis on a Stream of Features. EANN 2022: 223-234 - [c37]Jan Motl, Pavel Kordík:
Trend and Seasonality Elimination from Relational Data. EANN 2022: 260-268 - [c36]Petr Simánek, Daniel Vasata, Pavel Kordík:
Learning to Optimize with Dynamic Mode Decomposition. IJCNN 2022: 1-8 - [c35]Vojtech Vancura, Rodrigo Alves, Petr Kasalický, Pavel Kordík:
Scalable Linear Shallow Autoencoder for Collaborative Filtering. RecSys 2022: 604-609 - [c34]Jan Safarík, Vojtech Vancura, Pavel Kordík:
RepSys: Framework for Interactive Evaluation of Recommender Systems. RecSys 2022: 636-639 - [i4]Petr Simánek, Daniel Vasata, Pavel Kordík:
Learning to Optimize with Dynamic Mode Decomposition. CoRR abs/2211.16268 (2022) - 2021
- [c33]Tomás Chobola, Daniel Vasata, Pavel Kordík:
Transfer learning based few-shot classification using optimal transport mapping from preprocessed latent space of backbone neural network. MetaDL@AAAI 2021: 29-37 - [c32]Vojtech Vancura, Pavel Kordík:
Deep Variational Autoencoder with Shallow Parallel Path for Top-N Recommendation (VASP). ICANN (5) 2021: 138-149 - [c31]Alexander Kovalenko, Pavel Kordík, Magda Friedjungová:
Dynamic Neural Diversification: Path to Computationally Sustainable Neural Networks. ICANN (2) 2021: 235-247 - [c30]Jan Motl, Pavel Kordík:
Stratified Cross-Validation on Multiple Columns. ICTAI 2021: 26-31 - [c29]Jan Motl, Pavel Kordík:
Aggregate Function Generalization to Temporal Data. ICTAI 2021: 614-618 - [c28]Zdenek Buk, Michal Stepanovsky, Anezka Koterová, Jana Velemínská, Jaroslav Bruzek, Pavel Kordík:
Novel Data Mining-based Age-at-death Estimation Model using Adult Pubic Symphysis 3D Scans. ITAT 2021: 46-52 - [i3]Tomás Chobola, Daniel Vasata, Pavel Kordík:
Transfer learning based few-shot classification using optimal transport mapping from preprocessed latent space of backbone neural network. CoRR abs/2102.05176 (2021) - [i2]Vojtech Vancura, Pavel Kordík:
Deep Variational Autoencoder with Shallow Parallel Path for Top-N Recommendation (VASP). CoRR abs/2102.05774 (2021) - [i1]Alexander Kovalenko, Pavel Kordík, Magda Friedjungová:
Dynamic Neural Diversification: Path to Computationally Sustainable Neural Networks. CoRR abs/2109.09612 (2021)
2010 – 2019
- 2019
- [j4]Tomás Barton, Tomas Bruna, Pavel Kordík:
Chameleon 2: An Improved Graph-Based Clustering Algorithm. ACM Trans. Knowl. Discov. Data 13(1): 10 (2019) - [c27]Jan Motl, Pavel Kordík:
Learning on a Stream of Features with Random Forest. ITAT 2019: 79-83 - 2018
- [j3]Pavel Kordík, Ján Cerný, Tomás Frýda:
Discovering predictive ensembles for transfer learning and meta-learning. Mach. Learn. 107(1): 177-207 (2018) - [c26]Jan Motl, Pavel Kordík:
Do We Need to Observe Features to Perform Feature Selection? ITAT 2018: 44-51 - [c25]Jan Motl, Pavel Kordík:
Violation of Independence of Irrelevant Alternatives in Friedman's test. ITAT 2018: 59-63 - 2017
- [c24]Pavel Kordík, Tomás Frýda, Miroslav Snorek, Miroslav Cepek:
Scalability of predictive ensembles. CSIT (1) 2017: 555-560 - [c23]Jan Motl, Pavel Kordík:
Foreign Key Constraint Identification in Relational Databases. ITAT 2017: 106-111 - 2016
- [c22]Tomás Barton, Tomas Bruna, Pavel Kordík:
MoCham: Robust Hierarchical Clustering Based on Multi-objective Optimization. ICDM Workshops 2016: 831-838 - [c21]Jan Tkacik, Pavel Kordík:
Neural Turing Machine for sequential learning of human mobility patterns. IJCNN 2016: 2790-2797 - [c20]Stanislav Kuznetsov, Pavel Kordík, Tomas Rehorek, Josef Dvorak, Petr Kroha:
Reducing cold start problems in educational recommender systems. IJCNN 2016: 3143-3149 - 2015
- [c19]Pavel Kordík, Stanislav Kuznetsov:
Mining Skills from Educational Data for Project Recommendations. CISIS-ICEUTE 2015: 617-627 - [c18]Tomás Barton, Pavel Kordík:
Evaluation of Relative Indexes for Multi-objective Clustering. HAIS 2015: 465-476 - [c17]Tomás Barton, Pavel Kordík:
Using Multi-Objective Optimization for the Selection of Ensemble Members. ITAT 2015: 108-114 - 2014
- [c16]Pavel Kordík, Ján Cerný:
Building predictive models in two stages with meta-learning templates optimized by genetic programming. CIEL 2014: 27-34 - 2013
- [j2]Ondrej Hava, Miroslav Skrbek, Pavel Kordík:
Supervised two-step feature extraction for structured representation of text data. Simul. Model. Pract. Theory 33: 132-143 (2013) - 2012
- [c15]Oleg Kovárík, Pavel Kordík:
Max-min ant system with linear memory complexity. IEEE Congress on Evolutionary Computation 2012: 1-5 - [c14]Ondrej Hava, Miroslav Skrbek, Pavel Kordík:
Contextual Latent Semantic Networks used for Document Classification. KDIR 2012: 425-430 - [c13]Pavel Kordík, Ján Cerný:
On performance of meta-learning templates on different datasets. IJCNN 2012: 1-7 - [c12]Tomas Rehorek, Pavel Kordík:
A Soft Computing Approach to Knowledge Flow Synthesis and Optimization. SOCO 2012: 23-32 - [c11]Tomás Barton, Pavel Kordík:
Encoding Time Series Data for Better Clustering Results. CISIS/ICEUTE/SOCO Special Sessions 2012: 467-475 - [c10]Ondrej Hava, Miroslav Skrbek, Pavel Kordík:
Document classification with supervised latent feature selection. WIMS 2012: 70:1-70:4 - 2011
- [p1]Pavel Kordík, Ján Cerný:
Self-organization of Supervised Models. Meta-Learning in Computational Intelligence 2011: 179-223 - 2010
- [j1]Pavel Kordík, Jan Koutník, Jan Drchal, Oleg Kovárík, Miroslav Cepek, Miroslav Snorek:
Meta-learning approach to neural network optimization. Neural Networks 23(4): 568-582 (2010)
2000 – 2009
- 2009
- [c9]Pavel Kordík, Martin Hasaj, Marek Tvrdy, Miroslav Snorek:
Building Automation Simulator and Control Strategy for Intelligent and Energy Efficient Home. EMS 2009: 154-159 - 2008
- [c8]Daniel Novák, Ales Pilný, Pavel Kordík, Stefan Holiga, Petr Posík, R. Cerný, Richard Brzezny:
Analysis of Vestibular-Ocular Reflex by Evolutionary Framework. ICANN (1) 2008: 452-461 - [c7]Tomás Siegl, Pavel Kordík, Miroslav Snorek, Pavel Calda:
Fetal Weight Prediction Models: Standard Techniques or Computational Intelligence Methods?. ICANN (1) 2008: 462-471 - [c6]Pavel Kordík, Václav Kremen, Lenka Lhotská:
The GAME Algorithm Applied to Complex Fractionated Atrial Electrograms Data Set. ICANN (2) 2008: 859-868 - [c5]Ales Pilný, Pavel Kordík, Miroslav Snorek:
Feature Ranking Derived from Data Mining Process. ICANN (2) 2008: 889-898 - 2007
- [c4]Ivo Kondapaneni, Pavel Kordík, Pavel Slavík:
Visualization techniques utilizing the sensitivity analysis of models. WSC 2007: 730-737 - 2006
- [c3]Pavel Kordík, Jan Saidl, Miroslav Snorek:
Evolutionary Search for Interesting Behavior of Neural Network Ensembles. IJCNN 2006: 1290-1293 - 2005
- [c2]Pavel Kordík, Miroslav Snorek:
Ensemble Techniques for Credibility Estimation of GAME Models. ICANN (2) 2005: 127-132 - 2004
- [c1]Pavel Kordík, Miroslav Snorek, Marko Genyk-Berezovskyj:
Hybrid inductive models: deterministic crowding employed. IJCNN 2004: 2343-2346
Coauthor Index
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