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ORCIDStephen J. Roberts
Stephen Roberts 0001
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- affiliation: University of Oxford, UK
Other persons with the same name
- Stephen Roberts — disambiguation page
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2020 – today
- 2024
[j60]Diego Granziol, Nicholas P. Baskerville, Xingchen Wan, Samuel Albanie, Stephen Roberts:
Iterate Averaging in the Quest for Best Test Error. J. Mach. Learn. Res. 25: 20:1-20:55 (2024)- [j59]Harry Coppock, George Nicholson, Ivan Kiskin, Vasiliki Koutra, Kieran Baker
, Jobie Budd, Richard Payne, Emma Karoune, David Hurley, Alexander Titcomb, Sabrina Egglestone, Ana Tendero Cañadas, Lorraine Butler, Radka Jersakova, Jonathon Mellor, Selina Patel, Tracey Thornley, Peter Diggle, Sylvia Richardson, Josef Packham, Björn W. Schuller, Davide Pigoli, Steven G. Gilmour, Stephen J. Roberts, Christopher C. Holmes:
Audio-based AI classifiers show no evidence of improved COVID-19 screening over simple symptoms checkers. Nat. Mac. Intell. 6(2): 229-242 (2024) - [c120]Wee Ling Tan, Stephen Roberts, Stefan Zohren:
Deep Learning for Options Trading: An End-To-End Approach. ICAIF 2024: 487-495 - [i107]Wee Ling Tan, Stephen J. Roberts, Stefan Zohren:
Deep Learning for Options Trading: An End-To-End Approach. CoRR abs/2407.21791 (2024) - 2023
- [j58]Samuel Kessler, Adam D. Cobb, Tim G. J. Rudner, Stefan Zohren, Stephen J. Roberts:
On Sequential Bayesian Inference for Continual Learning. Entropy 25(6): 884 (2023) - [j57]Julien Walden Huang, Stephen J. Roberts, Jan-Peter Calliess:
On the Sample Complexity of Lipschitz Constant Estimation. Trans. Mach. Learn. Res. 2023 (2023) - [c119]Samuel Kessler, Mateusz Ostaszewski, Michal Pawel Bortkiewicz, Mateusz Zarski, Maciej Wolczyk, Jack Parker-Holder, Stephen J. Roberts, Piotr Milos:
The Effectiveness of World Models for Continual Reinforcement Learning. CoLLAs 2023: 184-204 - [c118]Scott Alexander Cameron, Arnu Pretorius, Stephen J. Roberts:
Nonparametric Boundary Geometry in Physics Informed Deep Learning. NeurIPS 2023 - [i106]Samuel Kessler, Adam D. Cobb, Tim G. J. Rudner, Stefan Zohren, Stephen J. Roberts:
On Sequential Bayesian Inference for Continual Learning. CoRR abs/2301.01828 (2023) - [i105]Wee Ling Tan, Stephen J. Roberts, Stefan Zohren:
Spatio-Temporal Momentum: Jointly Learning Time-Series and Cross-Sectional Strategies. CoRR abs/2302.10175 (2023) - [i104]Lawrence Wang, Stephen J. Roberts:
SANE: The phases of gradient descent through Sharpness Adjusted Number of Effective parameters. CoRR abs/2305.18490 (2023) - [i103]Lawrence Wang, Stephen Roberts:
The instabilities of large learning rate training: a loss landscape view. CoRR abs/2307.11948 (2023) - [i102]Xingyue Pu, Stephen J. Roberts, Xiaowen Dong, Stefan Zohren:
Network Momentum across Asset Classes. CoRR abs/2308.11294 (2023) - [i101]Xingyue Pu, Stefan Zohren, Stephen J. Roberts, Xiaowen Dong:
Learning to Learn Financial Networks for Optimising Momentum Strategies. CoRR abs/2308.12212 (2023) - [i100]Kieran Wood, Samuel Kessler, Stephen J. Roberts, Stefan Zohren:
Few-Shot Learning Patterns in Financial Time-Series for Trend-Following Strategies. CoRR abs/2310.10500 (2023) - 2022
- [j56]Diego Granziol, Binxin Ru, Xiaowen Dong, Stefan Zohren, Michael A. Osborne, Stephen J. Roberts:
Maximum Entropy Approach to Massive Graph Spectrum Learning with Applications. Algorithms 15(6): 209 (2022) - [j55]Andrea Patane, Arno Blaas, Luca Laurenti, Luca Cardelli, Stephen Roberts, Marta Kwiatkowska:
Adversarial Robustness Guarantees for Gaussian Processes. J. Mach. Learn. Res. 23: 146:1-146:55 (2022) - [j54]Diego Granziol, Stefan Zohren, Stephen Roberts:
Learning Rates as a Function of Batch Size: A Random Matrix Theory Approach to Neural Network Training. J. Mach. Learn. Res. 23: 173:1-173:65 (2022) - [c117]Samuel Kessler, Jack Parker-Holder, Philip J. Ball, Stefan Zohren, Stephen J. Roberts:
Same State, Different Task: Continual Reinforcement Learning without Interference. AAAI 2022: 7143-7151 - [c116]Saad Hamid, Sebastian Schulze, Michael A. Osborne, Stephen J. Roberts:
Marginalising over Stationary Kernels with Bayesian Quadrature. AISTATS 2022: 9776-9792 - [c115]Jaleh Zand, Jack Parker-Holder, Stephen J. Roberts:
On-the-fly Strategy Adaptation for ad-hoc Agent Coordination. AAMAS 2022: 1771-1773 - [c114]Shuyu Lin, Ronald Clark, Niki Trigoni, Stephen J. Roberts:
Uncertainty Estimation with a VAE-Classifier Hybrid Model. ICASSP 2022: 3548-3552 - [c113]Scott Alexander Cameron, Tyron Luke Cameron, Arnu Pretorius, Stephen J. Roberts:
Robust and Scalable SDE Learning: A Functional Perspective. ICLR 2022 - [c112]Cong Lu, Philip J. Ball, Jack Parker-Holder, Michael A. Osborne, Stephen J. Roberts:
Revisiting Design Choices in Offline Model Based Reinforcement Learning. ICLR 2022 - [c111]Edoardo Cetin, Philip J. Ball, Stephen J. Roberts, Oya Çeliktutan:
Stabilizing Off-Policy Deep Reinforcement Learning from Pixels. ICML 2022: 2784-2810 - [c110]Björn W. Schuller, Anton Batliner, Shahin Amiriparian, Christian Bergler, Maurice Gerczuk, Natalie Holz, Pauline Larrouy-Maestri, Sebastian P. Bayerl, Korbinian Riedhammer, Adria Mallol-Ragolta, Maria Pateraki, Harry Coppock, Ivan Kiskin, Marianne Sinka, Stephen J. Roberts:
The ACM Multimedia 2022 Computational Paralinguistics Challenge: Vocalisations, Stuttering, Activity, & Mosquitoes. ACM Multimedia 2022: 7120-7124 - [c109]Yingchen Xu, Jack Parker-Holder, Aldo Pacchiano, Philip J. Ball, Oleh Rybkin, Stephen Roberts, Tim Rocktäschel, Edward Grefenstette:
Learning General World Models in a Handful of Reward-Free Deployments. NeurIPS 2022 - [i99]Jaleh Zand, Jack Parker-Holder, Stephen J. Roberts:
On-the-fly Strategy Adaptation for ad-hoc Agent Coordination. CoRR abs/2203.08015 (2022) - [i98]Björn W. Schuller, Anton Batliner, Shahin Amiriparian, Christian Bergler, Maurice Gerczuk, Natalie Holz, Pauline Larrouy-Maestri, Sebastian P. Bayerl, Korbinian Riedhammer, Adria Mallol-Ragolta, Maria Pateraki, Harry Coppock, Ivan Kiskin, Marianne Sinka, Stephen J. Roberts:
The ACM Multimedia 2022 Computational Paralinguistics Challenge: Vocalisations, Stuttering, Activity, & Mosquitoes. CoRR abs/2205.06799 (2022) - [i97]Edoardo Cetin, Philip J. Ball, Stephen J. Roberts, Oya Çeliktutan:
Stabilizing Off-Policy Deep Reinforcement Learning from Pixels. CoRR abs/2207.00986 (2022) - [i96]Daniel Poh, Stephen J. Roberts, Stefan Zohren:
Transfer Ranking in Finance: Applications to Cross-Sectional Momentum with Data Scarcity. CoRR abs/2208.09968 (2022) - [i95]Yingchen Xu, Jack Parker-Holder, Aldo Pacchiano, Philip J. Ball, Oleh Rybkin, Stephen J. Roberts, Tim Rocktäschel, Edward Grefenstette:
Learning General World Models in a Handful of Reward-Free Deployments. CoRR abs/2210.12719 (2022) - [i94]Samuel Kessler, Piotr Milos, Jack Parker-Holder, Stephen J. Roberts:
The Surprising Effectiveness of Latent World Models for Continual Reinforcement Learning. CoRR abs/2211.15944 (2022) - [i93]Jobie Budd, Kieran Baker, Emma Karoune, Harry Coppock, Selina Patel, Ana Tendero Cañadas, Alexander Titcomb, Richard Payne, David Hurley, Sabrina Egglestone, Lorraine Butler, Jonathon Mellor, George Nicholson, Ivan Kiskin, Vasiliki Koutra, Radka Jersakova, Rachel A. McKendry, Peter Diggle, Sylvia Richardson, Björn W. Schuller, Steven Gilmour, Davide Pigoli, Stephen J. Roberts, Josef Packham, Tracey Thornley, Chris C. Holmes:
A large-scale and PCR-referenced vocal audio dataset for COVID-19. CoRR abs/2212.07738 (2022) - [i92]Harry Coppock, George Nicholson, Ivan Kiskin, Vasiliki Koutra, Kieran Baker, Jobie Budd, Richard Payne, Emma Karoune, David Hurley, Alexander Titcomb, Sabrina Egglestone, Ana Tendero Cañadas, Lorraine Butler, Radka Jersakova, Jonathon Mellor, Selina Patel, Tracey Thornley, Peter Diggle, Sylvia Richardson, Josef Packham, Björn W. Schuller, Davide Pigoli, Steven Gilmour, Stephen J. Roberts, Chris C. Holmes:
Audio-based AI classifiers show no evidence of improved COVID-19 screening over simple symptoms checkers. CoRR abs/2212.08570 (2022) - [i91]Davide Pigoli, Kieran Baker, Jobie Budd, Lorraine Butler, Harry Coppock, Sabrina Egglestone, Steven G. Gilmour, Chris C. Holmes, David Hurley, Radka Jersakova, Ivan Kiskin, Vasiliki Koutra, Jonathon Mellor, George Nicholson, Joe Packham, Selina Patel, Richard Payne, Stephen J. Roberts, Björn W. Schuller, Ana Tendero Cañadas, Tracey Thornley, Alexander Titcomb:
Statistical Design and Analysis for Robust Machine Learning: A Case Study from COVID-19. CoRR abs/2212.08571 (2022) - 2021
- [j53]Anup Aprem, Stephen Roberts:
A Bayesian Optimization Approach to Compute Nash Equilibrium of Potential Games Using Bandit Feedback. Comput. J. 64(12): 1801-1813 (2021) - [j52]Anup Aprem, Stephen J. Roberts:
Optimal pricing in black box producer-consumer Stackelberg games using revealed preference feedback. Neurocomputing 437: 31-41 (2021) - [c108]Alexander Camuto, Matthew Willetts, Stephen J. Roberts, Chris C. Holmes, Tom Rainforth:
Towards a Theoretical Understanding of the Robustness of Variational Autoencoders. AISTATS 2021: 3565-3573 - [c107]Alexander Camuto, Matthew Willetts, Chris C. Holmes, Brooks Paige, Stephen J. Roberts:
Learning Bijective Feature Maps for Linear ICA. AISTATS 2021: 3655-3663 - [c106]Matthew Willetts, Alexander Camuto, Tom Rainforth, Stephen J. Roberts, Christopher C. Holmes:
Improving VAEs' Robustness to Adversarial Attack. ICLR 2021 - [c105]Philip J. Ball, Cong Lu, Jack Parker-Holder, Stephen J. Roberts:
Augmented World Models Facilitate Zero-Shot Dynamics Generalization From a Single Offline Environment. ICML 2021: 619-629 - [c104]Ivan Kiskin, Marianne Sinka, Adam D. Cobb, Waqas Rafique, Lawrence Wang, Davide Zilli, Benjamin Gutteridge, Rinita Dam, Theodoros Marinos, Yunpeng Li, Dickson Msaky, Emmanuel Kaindoa, Gerard Killeen, Eva Herreros-Moya, Kathy Willis, Stephen J. Roberts:
HumBugDB: A Large-scale Acoustic Mosquito Dataset. NeurIPS Datasets and Benchmarks 2021 - [c103]Jack Parker-Holder, Vu Nguyen, Shaan Desai, Stephen J. Roberts:
Tuning Mixed Input Hyperparameters on the Fly for Efficient Population Based AutoRL. NeurIPS 2021: 15513-15528 - [c102]Ivan Kiskin, Adam D. Cobb, Marianne Sinka, Kathy Willis, Stephen J. Roberts:
Automatic Acoustic Mosquito Tagging with Bayesian Neural Networks. ECML/PKDD (4) 2021: 351-366 - [c101]Samuel Kessler, Vu Nguyen, Stefan Zohren, Stephen J. Roberts:
Hierarchical Indian buffet neural networks for Bayesian continual learning. UAI 2021: 749-759 - [c100]Aldo Pacchiano, Philip J. Ball, Jack Parker-Holder, Krzysztof Choromanski, Stephen Roberts:
Towards tractable optimism in model-based reinforcement learning. UAI 2021: 1413-1423 - [i90]Arno Blaas, Stephen J. Roberts:
The Effect of Prior Lipschitz Continuity on the Adversarial Robustness of Bayesian Neural Networks. CoRR abs/2101.02689 (2021) - [i89]Philip J. Ball, Stephen J. Roberts:
OffCon3: What is state of the art anyway? CoRR abs/2101.11331 (2021) - [i88]Andrea Patane, Arno Blaas, Luca Laurenti, Luca Cardelli, Stephen J. Roberts, Marta Kwiatkowska:
Adversarial Robustness Guarantees for Gaussian Processes. CoRR abs/2104.03180 (2021) - [i87]Philip J. Ball, Cong Lu, Jack Parker-Holder, Stephen J. Roberts:
Augmented World Models Facilitate Zero-Shot Dynamics Generalization From a Single Offline Environment. CoRR abs/2104.05632 (2021) - [i86]Daniel Poh, Bryan Lim, Stefan Zohren, Stephen J. Roberts:
Enhancing Cross-Sectional Currency Strategies by Ranking Refinement with Transformer-based Architectures. CoRR abs/2105.10019 (2021) - [i85]Kieran Wood, Stephen J. Roberts, Stefan Zohren:
Slow Momentum with Fast Reversion: A Trading Strategy Using Deep Learning and Changepoint Detection. CoRR abs/2105.13727 (2021) - [i84]Lewis Smith, Joost van Amersfoort, Haiwen Huang, Stephen J. Roberts, Yarin Gal:
Can convolutional ResNets approximately preserve input distances? A frequency analysis perspective. CoRR abs/2106.02469 (2021) - [i83]Samuel Kessler, Jack Parker-Holder, Philip J. Ball, Stefan Zohren, Stephen J. Roberts:
Same State, Different Task: Continual Reinforcement Learning without Interference. CoRR abs/2106.02940 (2021) - [i82]Saad Hamid, Sebastian Schulze, Michael A. Osborne, Stephen J. Roberts:
Marginalising over Stationary Kernels with Bayesian Quadrature. CoRR abs/2106.07452 (2021) - [i81]Jack Parker-Holder, Vu Nguyen, Shaan Desai, Stephen J. Roberts:
Tuning Mixed Input Hyperparameters on the Fly for Efficient Population Based AutoRL. CoRR abs/2106.15883 (2021) - [i80]Shaan Desai, Marios Mattheakis, David Sondak, Pavlos Protopapas, Stephen J. Roberts:
Port-Hamiltonian Neural Networks for Learning Explicit Time-Dependent Dynamical Systems. CoRR abs/2107.08024 (2021) - [i79]Cong Lu, Philip J. Ball, Jack Parker-Holder, Michael A. Osborne, Stephen J. Roberts:
Revisiting Design Choices in Model-Based Offline Reinforcement Learning. CoRR abs/2110.04135 (2021) - [i78]Scott Alexander Cameron, Tyron Luke Cameron, Arnu Pretorius, Stephen J. Roberts:
Robust and Scalable SDE Learning: A Functional Perspective. CoRR abs/2110.05167 (2021) - [i77]Ivan Kiskin, Marianne Sinka, Adam D. Cobb, Waqas Rafique, Lawrence Wang, Davide Zilli, Benjamin Gutteridge, Rinita Dam, Theodoros Marinos, Yunpeng Li, Dickson Msaky, Emmanuel Kaindoa, Gerard Killeen, Eva Herreros-Moya, Kathy J. Willis, Stephen J. Roberts:
HumBugDB: A Large-scale Acoustic Mosquito Dataset. CoRR abs/2110.07607 (2021) - [i76]Shaan Desai, Marios Mattheakis, Hayden Joy, Pavlos Protopapas, Stephen J. Roberts:
One-Shot Transfer Learning of Physics-Informed Neural Networks. CoRR abs/2110.11286 (2021) - [i75]Kieran Wood, Sven Giegerich, Stephen J. Roberts, Stefan Zohren:
Trading with the Momentum Transformer: An Intelligent and Interpretable Architecture. CoRR abs/2112.08534 (2021) - 2020
- [j51]Jan-Peter Calliess, Stephen J. Roberts, Carl Edward Rasmussen, Jan M. Maciejowski:
Lazily Adapted Constant Kinky Inference for nonparametric regression and model-reference adaptive control. Autom. 122: 109216 (2020) - [j50]Ivan Kiskin, Davide Zilli, Yunpeng Li, Marianne Sinka, Kathy Willis, Stephen J. Roberts:
Bioacoustic detection with wavelet-conditioned convolutional neural networks. Neural Comput. Appl. 32(4): 915-927 (2020) - [c99]Arno Blaas, Andrea Patane, Luca Laurenti, Luca Cardelli, Marta Kwiatkowska, Stephen J. Roberts:
Adversarial Robustness Guarantees for Classification with Gaussian Processes. AISTATS 2020: 3372-3382 - [c98]Matthew Willetts, Stephen J. Roberts, Chris C. Holmes:
Semi-Unsupervised Learning: Clustering and Classifying using Ultra-Sparse Labels. IEEE BigData 2020: 5286-5295 - [c97]Kyriakos Polymenakos, Luca Laurenti, Andrea Patane, Jan-Peter Calliess, Luca Cardelli, Marta Kwiatkowska, Alessandro Abate, Stephen J. Roberts:
Safety Guarantees for Iterative Predictions with Gaussian Processes. CDC 2020: 3187-3193 - [c96]Bernardo Pérez Orozco, Stephen J. Roberts:
Zero-shot and few-shot time series forecasting with ordinal regression recurrent neural networks. ESANN 2020: 503-508 - [c95]Bingqing Liu, Ivan Kiskin, Stephen Roberts:
An Overview of Gaussian process Regression for Volatility Forecasting. ICAIIC 2020: 681-686 - [c94]Ivan Kiskin, Adam D. Cobb, Lawrence Wang, Stephen Roberts:
Humbug Zooniverse: A Crowd-Sourced Acoustic Mosquito Dataset. ICASSP 2020: 916-920 - [c93]Shuyu Lin, Ronald Clark, Robert Birke, Sandro Schönborn, Niki Trigoni, Stephen J. Roberts:
Anomaly Detection for Time Series Using VAE-LSTM Hybrid Model. ICASSP 2020: 4322-4326 - [c92]Philip J. Ball, Jack Parker-Holder, Aldo Pacchiano, Krzysztof Choromanski, Stephen J. Roberts:
Ready Policy One: World Building Through Active Learning. ICML 2020: 591-601 - [c91]Bin Xin Ru, Ahsan S. Alvi, Vu Nguyen, Michael A. Osborne, Stephen J. Roberts:
Bayesian Optimisation over Multiple Continuous and Categorical Inputs. ICML 2020: 8276-8285 - [c90]Bryan Lim, Stefan Zohren, Stephen Roberts:
Recurrent Neural Filters: Learning Independent Bayesian Filtering Steps for Time Series Prediction. IJCNN 2020: 1-8 - [c89]Alexander Camuto, Matthew Willetts, Umut Simsekli, Stephen J. Roberts, Chris C. Holmes:
Explicit Regularisation in Gaussian Noise Injections. NeurIPS 2020 - [c88]Jack Parker-Holder, Vu Nguyen, Stephen J. Roberts:
Provably Efficient Online Hyperparameter Optimization with Population-Based Bandits. NeurIPS 2020 - [c87]Jack Parker-Holder, Aldo Pacchiano, Krzysztof Marcin Choromanski, Stephen J. Roberts:
Effective Diversity in Population Based Reinforcement Learning. NeurIPS 2020 - [c86]Kyriakos Polymenakos, Nikitas Rontsis, Alessandro Abate, Stephen J. Roberts:
SafePILCO: A Software Tool for Safe and Data-Efficient Policy Synthesis. QEST 2020: 18-26 - [i74]Ivan Kiskin, Adam D. Cobb, Lawrence Wang, Stephen Roberts:
HumBug Zooniverse: a crowd-sourced acoustic mosquito dataset. CoRR abs/2001.04733 (2020) - [i73]Jack Parker-Holder, Aldo Pacchiano, Krzysztof Choromanski, Stephen Roberts:
Effective Diversity in Population-Based Reinforcement Learning. CoRR abs/2002.00632 (2020) - [i72]Bryan Lim, Stefan Zohren, Stephen Roberts:
Detecting Changes in Asset Co-Movement Using the Autoencoder Reconstruction Ratio. CoRR abs/2002.02008 (2020) - [i71]Jack Parker-Holder, Vu Nguyen, Stephen Roberts:
One-Shot Bayes Opt with Probabilistic Population Based Training. CoRR abs/2002.02518 (2020) - [i70]Philip J. Ball, Jack Parker-Holder, Aldo Pacchiano, Krzysztof Choromanski, Stephen Roberts:
Ready Policy One: World Building Through Active Learning. CoRR abs/2002.02693 (2020) - [i69]Alexander Camuto, Matthew Willetts, Brooks Paige, Chris C. Holmes, Stephen J. Roberts:
Learning Bijective Feature Maps for Linear ICA. CoRR abs/2002.07766 (2020) - [i68]Diego Granziol, Xingchen Wan, Stephen Roberts:
Iterate Averaging Helps: An Alternative Perspective in Deep Learning. CoRR abs/2003.01247 (2020) - [i67]Bernardo Pérez Orozco, Stephen J. Roberts:
Zero-shot and few-shot time series forecasting with ordinal regression recurrent neural networks. CoRR abs/2003.12162 (2020) - [i66]Jaleh Zand, Stephen Roberts:
Mixture Density Conditional Generative Adversarial Network Models (MD-CGAN). CoRR abs/2004.03797 (2020) - [i65]Shaan Desai, Stephen Roberts:
VIGN: Variational Integrator Graph Networks. CoRR abs/2004.13688 (2020) - [i64]Zihao Zhang, Stefan Zohren, Stephen Roberts:
Deep Learning for Portfolio Optimisation. CoRR abs/2005.13665 (2020) - [i63]Aldo Pacchiano, Philip J. Ball, Jack Parker-Holder, Krzysztof Choromanski, Stephen Roberts:
On Optimism in Model-Based Reinforcement Learning. CoRR abs/2006.11911 (2020) - [i62]Matthew Willetts, Xenia Miscouridou, Stephen J. Roberts, Chris C. Holmes:
Relaxed-Responsibility Hierarchical Discrete VAEs. CoRR abs/2007.07307 (2020) - [i61]Alexander Camuto, Matthew Willetts, Stephen J. Roberts, Chris C. Holmes, Tom Rainforth:
Towards a Theoretical Understanding of the Robustness of Variational Autoencoders. CoRR abs/2007.07365 (2020) - [i60]Alexander Camuto, Matthew Willetts, Umut Simsekli, Stephen J. Roberts, Chris C. Holmes:
Explicit Regularisation in Gaussian Noise Injections. CoRR abs/2007.07368 (2020) - [i59]Kyriakos Polymenakos, Nikitas Rontsis, Alessandro Abate, Stephen J. Roberts:
SafePILCO: a software tool for safe and data-efficient policy synthesis. CoRR abs/2008.03273 (2020) - [i58]Diego Granziol, Samuel Albanie, Xingchen Wan, Stephen J. Roberts:
Explaining the Adaptive Generalisation Gap. CoRR abs/2011.08181 (2020) - [i57]Daniel Poh, Bryan Lim, Stefan Zohren, Stephen J. Roberts:
Building Cross-Sectional Systematic Strategies By Learning to Rank. CoRR abs/2012.07149 (2020)
2010 – 2019
- 2019
- [j49]Diego Granziol, Bin Xin Ru, Stefan Zohren, Xiaowen Dong, Michael A. Osborne, Stephen J. Roberts:
MEMe: An Accurate Maximum Entropy Method for Efficient Approximations in Large-Scale Machine Learning. Entropy 21(6): 551 (2019) - [j48]Jack K. Fitzsimons, AbdulRahman Al Ali, Michael A. Osborne, Stephen J. Roberts:
A General Framework for Fair Regression. Entropy 21(8): 741 (2019) - [j47]Glen Wright Colopy, Stephen J. Roberts, David A. Clifton:
Gaussian Processes for Personalized Interpretable Volatility Metrics in the Step-Down Ward. IEEE J. Biomed. Health Informatics 23(3): 949-959 (2019) - [j46]Zihao Zhang, Stefan Zohren, Stephen J. Roberts:
DeepLOB: Deep Convolutional Neural Networks for Limit Order Books. IEEE Trans. Signal Process. 67(11): 3001-3012 (2019) - [c85]Kyriakos Polymenakos, Alessandro Abate, Stephen J. Roberts:
Safe Policy Search Using Gaussian Process Models. AAMAS 2019: 1565-1573 - [c84]Richard Everett, Adam D. Cobb, Andrew Markham, Stephen J. Roberts:
Optimising Worlds to Evaluate and Influence Reinforcement Learning Agents. AAMAS 2019: 1943-1945 - [c83]Shuyu Lin, Ronald Clark, Robert Birke, Niki Trigoni, Stephen J. Roberts:
WiSE-ALE: Wide Sample Estimator for Aggregate Latent Embedding. DGS@ICLR 2019 - [c82]Ahsan S. Alvi, Bin Xin Ru, Jan-Peter Calliess, Stephen J. Roberts, Michael A. Osborne:
Asynchronous Batch Bayesian Optimisation with Improved Local Penalisation. ICML 2019: 253-262 - [c81]Anup Aprem, Stephen J. Roberts:
Optimal Pricing In Black Box Producer-Consumer Stackelberg Games Using Revealed Preference Feedback. MLSP 2019: 1-6 - [i56]Bryan Lim, Stefan Zohren, Stephen J. Roberts:
Recurrent Neural Filters: Learning Independent Bayesian Filtering Steps for Time Series Prediction. CoRR abs/1901.08096 (2019) - [i55]Matthew Willetts, Stephen J. Roberts, Christopher C. Holmes:
Semi-Unsupervised Learning with Deep Generative Models: Clustering and Classifying using Ultra-Sparse Labels. CoRR abs/1901.08560 (2019) - [i54]Ahsan S. Alvi, Bin Xin Ru, Jan Calliess, Stephen J. Roberts, Michael A. Osborne:
Asynchronous Batch Bayesian Optimisation with Improved Local Penalisation. CoRR abs/1901.10452 (2019) - [i53]Shuyu Lin, Ronald Clark, Robert Birke, Niki Trigoni, Stephen J. Roberts:
WiSE-VAE: Wide Sample Estimator VAE. CoRR abs/1902.06160 (2019) - [i52]Edwin Simpson, Steven Reece, Stephen J. Roberts:
Bayesian Heatmaps: Probabilistic Classification with Multiple Unreliable Information Sources. CoRR abs/1904.03063 (2019) - [i51]Bryan Lim, Stefan Zohren, Stephen J. Roberts:
Enhancing Time Series Momentum Strategies Using Deep Neural Networks. CoRR abs/1904.04912 (2019) - [i50]Bryan Lim, Stefan Zohren, Stephen J. Roberts:
Population-based Global Optimisation Methods for Learning Long-term Dependencies with RNNs. CoRR abs/1905.09691 (2019) - [i49]Arno Blaas, Luca Laurenti, Andrea Patane, Luca Cardelli, Marta Kwiatkowska, Stephen J. Roberts:
Robustness Quantification for Classification with Gaussian Processes. CoRR abs/1905.11876 (2019) - [i48]Matthew Willetts, Alexander Camuto, Stephen J. Roberts, Chris C. Holmes:
Disentangling Improves VAEs' Robustness to Adversarial Attacks. CoRR abs/1906.00230 (2019) - [i47]Diego Granziol, Bin Xin Ru, Stefan Zohren, Xiaowen Dong, Michael A. Osborne, Stephen J. Roberts:
MEMe: An Accurate Maximum Entropy Method for Efficient Approximations in Large-Scale Machine Learning. CoRR abs/1906.01101 (2019) - [i46]Bin Xin Ru, Ahsan S. Alvi, Vu Nguyen, Michael A. Osborne, Stephen J. Roberts:
Bayesian Optimisation over Multiple Continuous and Categorical Inputs. CoRR abs/1906.08878 (2019) - [i45]Favour M. Nyikosa, Michael A. Osborne, Stephen J. Roberts:
Adaptive Configuration Oracle for Online Portfolio Selection Methods. CoRR abs/1908.08258 (2019) - [i44]Shuyu Lin, Stephen J. Roberts, Niki Trigoni, Ronald Clark:
Balancing Reconstruction Quality and Regularisation in ELBO for VAEs. CoRR abs/1909.03765 (2019) - [i43]Matthew Willetts, Stephen J. Roberts, Chris C. Holmes:
Disentangling to Cluster: Gaussian Mixture Variational Ladder Autoencoders. CoRR abs/1909.11501 (2019) - [i42]Matthew Willetts, Alexander Camuto, Stephen J. Roberts, Chris C. Holmes:
Regularising Deep Networks with DGMs. CoRR abs/1909.11507 (2019) - [i41]Adam D. Cobb, Atilim Günes Baydin, Andrew Markham, Stephen J. Roberts:
Introducing an Explicit Symplectic Integration Scheme for Riemannian Manifold Hamiltonian Monte Carlo. CoRR abs/1910.06243 (2019) - [i40]Zihao Zhang, Stefan Zohren, Stephen J. Roberts:
Deep Reinforcement Learning for Trading. CoRR abs/1911.10107 (2019) - [i39]Kyriakos Polymenakos, Luca Laurenti, Andrea Patane, Jan-Peter Calliess, Luca Cardelli, Marta Kwiatkowska, Alessandro Abate, Stephen J. Roberts:
Safety Guarantees for Planning Based on Iterative Gaussian Processes. CoRR abs/1912.00071 (2019) - [i38]Jack K. Fitzsimons, Sebastian M. Schmon, Stephen J. Roberts:
Implicit Priors for Knowledge Sharing in Bayesian Neural Networks. CoRR abs/1912.00874 (2019) - [i37]Samuel Kessler, Vu Nguyen, Stefan Zohren, Stephen Roberts:
Indian Buffet Neural Networks for Continual Learning. CoRR abs/1912.02290 (2019) - [i36]Diego Granziol, Robin Ru, Stefan Zohren, Xiaowen Dong, Michael A. Osborne, Stephen J. Roberts:
A Maximum Entropy approach to Massive Graph Spectra. CoRR abs/1912.09068 (2019) - [i35]Diego Granziol, Xingchen Wan, Timur Garipov, Dmitry P. Vetrov, Stephen Roberts:
MLRG Deep Curvature. CoRR abs/1912.09656 (2019) - 2018
- [j45]Trung Dong Huynh, Mark Ebden, Joel E. Fischer, Stephen J. Roberts, Luc Moreau:
Provenance Network Analytics - An approach to data analytics using data provenance. Data Min. Knowl. Discov. 32(3): 708-735 (2018) - [j44]Glen Wright Colopy, Stephen J. Roberts, David A. Clifton:
Bayesian Optimization of Personalized Models for Patient Vital-Sign Monitoring. IEEE J. Biomed. Health Informatics 22(2): 301-310 (2018) - [c80]Oliver Bent, Sekou L. Remy, Stephen J. Roberts, Aisha Walcott-Bryant:
Novel Exploration Techniques (NETs) for Malaria Policy Interventions. AAAI 2018: 7735-7740 - [c79]Richard Everett, Stephen J. Roberts:
Learning Against Non-Stationary Agents with Opponent Modelling and Deep Reinforcement Learning. AAAI Spring Symposia 2018 - [c78]Jan-Peter Calliess, Antonis Papachristodoulou, Stephen J. Roberts:
Bayesian Nonparametrics and Feedback-Linearisation of Discretised Control-Affine Systems. CDC 2018: 6086-6093 - [c77]Yunpeng Li, Ivan Kiskin, Marianne Sinka, Davide Zilli, Henry Chan, Eva Herreros-Moya, Theeraphap Chareonviriyaphap, Rungarun Tisgratog, Kathy Willis, Stephen J. Roberts:
Fast mosquito acoustic detection with field cup recordings: an initial investigation. DCASE 2018: 153-157 - [c76]Jan-Peter Calliess, Stephen J. Roberts, Carl E. Rasmussen, Jan M. Maciejowski:
Nonlinear Set Membership Regression with Adaptive Hyper-Parameter Estimation for Online Learning and Control. ECC 2018: 1-6 - [c75]Mark McLeod, Stephen J. Roberts, Michael A. Osborne:
Optimization, Fast and Slow: Optimally Switching between Local and Bayesian Optimization. ICML 2018: 3440-3449 - [c74]Adam D. Cobb, Richard Everett, Andrew Markham, Stephen J. Roberts:
Identifying Sources and Sinks in the Presence of Multiple Agents with Gaussian Process Vector Calculus. KDD 2018: 1254-1262 - [c73]Arno Blaas, Adam D. Cobb, Jan-Peter Calliess, Stephen J. Roberts:
Scalable Bounding of Predictive Uncertainty in Regression Problems with SLAC. SUM 2018: 373-379 - [c72]Jack K. Fitzsimons, Michael A. Osborne, Stephen J. Roberts, Joseph Francis Fitzsimons:
Improved Stochastic Trace Estimation using Mutually Unbiased Bases. UAI 2018: 310-318 - [i34]Diego Granziol, Edward Wagstaff, Bin Xin Ru, Michael A. Osborne, Stephen J. Roberts:
VBALD - Variational Bayesian Approximation of Log Determinants. CoRR abs/1802.08054 (2018) - [i33]Adam D. Cobb, Richard Everett, Andrew Markham, Stephen J. Roberts:
Identifying Sources and Sinks in the Presence of Multiple Agents with Gaussian Process Vector Calculus. CoRR abs/1802.10446 (2018) - [i32]Mariano Chouza, Stephen J. Roberts, Stefan Zohren:
Gradient descent in Gaussian random fields as a toy model for high-dimensional optimisation in deep learning. CoRR abs/1803.09119 (2018) - [i31]Bernardo Pérez Orozco, Gabriele Abbati, Stephen J. Roberts:
MOrdReD: Memory-based Ordinal Regression Deep Neural Networks for Time Series Forecasting. CoRR abs/1803.09704 (2018) - [i30]Zhikuan Zhao, Jack K. Fitzsimons, Michael A. Osborne, Stephen J. Roberts, Joseph F. Fitzsimons:
Quantum algorithms for training Gaussian Processes. CoRR abs/1803.10520 (2018) - [i29]Diego Granziol, Bin Xin Ru, Stefan Zohren, Xiaowen Dong, Michael A. Osborne, Stephen J. Roberts:
Entropic Spectral Learning in Large Scale Networks. CoRR abs/1804.06802 (2018) - [i28]Adam D. Cobb, Stephen J. Roberts, Yarin Gal:
Loss-Calibrated Approximate Inference in Bayesian Neural Networks. CoRR abs/1805.03901 (2018) - [i27]Mark McLeod, Michael A. Osborne, Stephen J. Roberts:
Optimization, fast and slow: optimally switching between local and Bayesian optimization. CoRR abs/1805.08610 (2018) - [i26]Martin Tegner, Benjamin Bloem-Reddy, Stephen J. Roberts:
Sequential sampling of Gaussian process latent variable models. CoRR abs/1807.04932 (2018) - [i25]Timos Papadopoulos, Stephen J. Roberts, Katherine J. Willis:
Automated bird sound recognition in realistic settings. CoRR abs/1809.01133 (2018) - [i24]Jack K. Fitzsimons, AbdulRahman Al Ali, Michael A. Osborne, Stephen J. Roberts:
Equality Constrained Decision Trees: For the Algorithmic Enforcement of Group Fairness. CoRR abs/1810.05041 (2018) - [i23]Matthew Willetts, Aiden R. Doherty, Stephen J. Roberts, Chris C. Holmes:
Semi-unsupervised Learning of Human Activity using Deep Generative Models. CoRR abs/1810.12176 (2018) - [i22]Arnold Salas, Stefan Zohren, Stephen J. Roberts:
Practical Bayesian Learning of Neural Networks via Adaptive Subgradient Methods. CoRR abs/1811.03679 (2018) - [i21]Anup Aprem, Stephen J. Roberts:
A Bayesian optimization approach to compute the Nash equilibria of potential games using bandit feedback. CoRR abs/1811.06503 (2018) - [i20]Jack K. Fitzsimons, Michael A. Osborne, Stephen J. Roberts:
Intersectionality: Multiple Group Fairness in Expectation Constraints. CoRR abs/1811.09960 (2018) - [i19]Olga Isupova, Yunpeng Li, Danil Kuzin, Stephen J. Roberts, Katherine J. Willis, Steven Reece:
BCCNet: Bayesian classifier combination neural network. CoRR abs/1811.12258 (2018) - [i18]Wolfgang Fruehwirt, Adam D. Cobb, Martin Mairhofer, Leonard Weydemann, Heinrich Garn, Reinhold Schmidt, Thomas Benke, Peter Dal-Bianco, Gerhard Ransmayr, Markus Waser, Dieter Grossegger, Pengfei Zhang, Georg Dorffner, Stephen J. Roberts:
Bayesian deep neural networks for low-cost neurophysiological markers of Alzheimer's disease severity. CoRR abs/1812.04994 (2018) - 2017
- [c71]Syed Ali Asad Rizvi, Elmarie van Heerden, Arnold Salas, Favour Nyikosa, Stephen J. Roberts, Michael A. Osborne, Elmer Rodriguez:
Identifying Sources of Discrimination Risk in the Life Cycle of Machine Intelligence Applications under New European Union Regulations. AAAI Spring Symposia 2017 - [c70]Justin Bewsher, Alessandra Tosi, Michael A. Osborne, Stephen J. Roberts:
Distribution of Gaussian Process Arc Lengths. AISTATS 2017: 1412-1420 - [c69]Glen Wright Colopy, Marco A. F. Pimentel, Stephen J. Roberts, David A. Clifton:
Bayesian optimisation of Gaussian processes for identifying the deteriorating patient. BHI 2017: 85-88 - [c68]Diego Granziol, Stephen J. Roberts:
Entropic determinants of massive matrices. IEEE BigData 2017: 88-93 - [c67]Glen Wright Colopy, Tingting Zhu, Lei A. Clifton, Stephen J. Roberts, David A. Clifton:
Likelihood-based artefact detection in continuously-acquired patient vital signs. EMBC 2017: 2146-2149 - [c66]Edwin Simpson, Steven Reece, Stephen J. Roberts:
Bayesian Heatmaps: Probabilistic Classification with Multiple Unreliable Information Sources. ECML/PKDD (2) 2017: 109-125 - [c65]Dieter Hendricks, Stephen J. Roberts:
Optimal Client Recommendation for Market Makers in Illiquid Financial Products. ECML/PKDD (3) 2017: 166-178 - [c64]Jack K. Fitzsimons, Diego Granziol, Kurt Cutajar, Michael A. Osborne, Maurizio Filippone, Stephen J. Roberts:
Entropic Trace Estimates for Log Determinants. ECML/PKDD (1) 2017: 323-338 - [c63]Jack K. Fitzsimons, Kurt Cutajar, Maurizio Filippone, Michael A. Osborne, Stephen J. Roberts:
Bayesian Inference of Log Determinants. UAI 2017 - [i17]Jack K. Fitzsimons, Kurt Cutajar, Michael A. Osborne, Stephen J. Roberts, Maurizio Filippone:
Bayesian Inference of Log Determinants. CoRR abs/1704.01445 (2017) - [i16]Jack K. Fitzsimons, Diego Granziol, Kurt Cutajar, Michael A. Osborne, Maurizio Filippone, Stephen J. Roberts:
Entropic Trace Estimates for Log Determinants. CoRR abs/1704.07223 (2017) - [i15]Dieter Hendricks, Stephen J. Roberts:
Optimal client recommendation for market makers in illiquid financial products. CoRR abs/1704.08488 (2017) - [i14]Syed Ali Asad Rizvi, Stephen J. Roberts, Michael A. Osborne, Favour Nyikosa:
A Novel Approach to Forecasting Financial Volatility with Gaussian Process Envelopes. CoRR abs/1705.00891 (2017) - [i13]Ivan Kiskin, Bernardo Pérez Orozco, Theo Windebank, Davide Zilli, Marianne Sinka, Kathy Willis, Stephen J. Roberts:
Mosquito Detection with Neural Networks: The Buzz of Deep Learning. CoRR abs/1705.05180 (2017) - [i12]Adam D. Cobb, Andrew Markham, Stephen J. Roberts:
Learning from lions: inferring the utility of agents from their trajectories. CoRR abs/1709.02357 (2017) - [i11]Yunpeng Li, Davide Zilli, Henry C. B. Chan, Ivan Kiskin, Marianne Sinka, Stephen J. Roberts, Kathy Willis:
Mosquito detection with low-cost smartphones: data acquisition for malaria research. CoRR abs/1711.06346 (2017) - [i10]Oliver Bent, Sekou L. Remy, Stephen J. Roberts, Aisha Walcott-Bryant:
Novel Exploration Techniques (NETs) for Malaria Policy Interventions. CoRR abs/1712.00428 (2017) - [i9]Yunpeng Li, Ivan Kiskin, Davide Zilli, Marianne Sinka, Henry C. B. Chan, Kathy Willis, Stephen J. Roberts:
Cost-sensitive detection with variational autoencoders for environmental acoustic sensing. CoRR abs/1712.02488 (2017) - [i8]Kyriakos Polymenakos, Alessandro Abate, Stephen J. Roberts:
Safe Policy Search with Gaussian Process Models. CoRR abs/1712.05556 (2017) - 2016
- [j43]Sarvapali D. Ramchurn, Feng Wu, Wenchao Jiang, Joel E. Fischer, Steven Reece, Stephen J. Roberts, Tom Rodden, Chris Greenhalgh, Nicholas R. Jennings:
Human-agent collaboration for disaster response. Auton. Agents Multi Agent Syst. 30(1): 82-111 (2016) - [j42]Sarvapali D. Ramchurn, Trung Dong Huynh, Feng Wu, Yuki Ikuno, Jack Flann, Luc Moreau, Joel E. Fischer, Wenchao Jiang, Tom Rodden, Edwin Simpson, Steven Reece, Stephen J. Roberts, Nicholas R. Jennings:
A Disaster Response System based on Human-Agent Collectives. J. Artif. Intell. Res. 57: 661-708 (2016) - [j41]Yves-Laurent Kom Samo, Stephen J. Roberts:
String and Membrane Gaussian Processes. J. Mach. Learn. Res. 17: 131:1-131:87 (2016) - [c62]Chris M. Lloyd, Tom Gunter, Michael A. Osborne, Stephen J. Roberts, Tom Nickson:
Latent Point Process Allocation. AISTATS 2016: 389-397 - [c61]Glen Wright Colopy, Marco A. F. Pimentel, Stephen J. Roberts, David A. Clifton:
Bayesian Gaussian processes for identifying the deteriorating patient. EMBC 2016: 5311-5314 - [i7]Jack K. Fitzsimons, Michael A. Osborne, Stephen J. Roberts, Joseph F. Fitzsimons:
Improved stochastic trace estimation using mutually unbiased bases. CoRR abs/1608.00117 (2016) - 2015
- [j40]Siddhartha Ghosh, Steven Reece, Alex Rogers, Stephen J. Roberts, Areej Malibari, Nicholas R. Jennings:
Modeling the Thermal Dynamics of Buildings: A Latent-Force- Model-Based Approach. ACM Trans. Intell. Syst. Technol. 6(1): 7:1-7:27 (2015) - [c60]Sarvapali D. Ramchurn, Trung Dong Huynh, Yuki Ikuno, Jack Flann, Feng Wu, Luc Moreau, Nicholas R. Jennings, Joel E. Fischer, Wenchao Jiang, Tom Rodden, Edwin Simpson, Steven Reece, Stephen J. Roberts:
HAC-ER: A Disaster Response System based on Human-Agent Collectives. AAMAS 2015: 533-541 - [c59]Sarvapali D. Ramchurn, Trung Dong Huynh, Yuki Ikuno, Jack Flann, Feng Wu, Luc Moreau, Nicholas R. Jennings, Joel E. Fischer, Wenchao Jiang, Tom Rodden, Edwin Simpson, Steven Reece, Stephen J. Roberts:
HAC-ER: A Disaster Response System based on Human-Agent Collectives. AAMAS 2015: 1921-1922 - [c58]Chris M. Lloyd, Tom Gunter, Michael A. Osborne, Stephen J. Roberts:
Variational Inference for Gaussian Process Modulated Poisson Processes. ICML 2015: 1814-1822 - [c57]Yves-Laurent Kom Samo, Stephen J. Roberts:
Scalable Nonparametric Bayesian Inference on Point Processes with Gaussian Processes. ICML 2015: 2227-2236 - [c56]Edwin Simpson, Matteo Venanzi, Steven Reece, Pushmeet Kohli, John Guiver, Stephen J. Roberts, Nicholas R. Jennings:
Language Understanding in the Wild: Combining Crowdsourcing and Machine Learning. WWW 2015: 992-1002 - [p4]Edwin Simpson, Stephen J. Roberts:
Bayesian Methods for Intelligent Task Assignment in Crowdsourcing Systems. Decision Making 2015: 1-32 - [i6]Ibrahim A. Almosallam, Sam N. Lindsay, Matt J. Jarvis, Stephen J. Roberts:
A Sparse Gaussian Process Framework for Photometric Redshift Estimation. CoRR abs/1505.05489 (2015) - [i5]Timos Papadopoulos, Stephen J. Roberts, Kathy Willis:
Detecting bird sound in unknown acoustic background using crowdsourced training data. CoRR abs/1505.06443 (2015) - 2014
- [j39]Nicholas R. Jennings, Luc Moreau, David Nicholson, Sarvapali D. Ramchurn, Stephen J. Roberts, Tom Rodden, Alex Rogers:
Human-agent collectives. Commun. ACM 57(12): 80-88 (2014) - [j38]Steven Reece, Siddhartha Ghosh, Alex Rogers, Stephen J. Roberts, Nicholas R. Jennings:
Efficient state-space inference of periodic latent force models. J. Mach. Learn. Res. 15(1): 2337-2397 (2014) - [j37]Mark Smith, Steven Reece, Stephen J. Roberts, Ioannis Psorakis, Iead Rezek:
Maritime abnormality detection using Gaussian processes. Knowl. Inf. Syst. 38(3): 717-741 (2014) - [c55]Jan-Peter Calliess, Michael A. Osborne, Stephen J. Roberts:
Conservative collision prediction and avoidance for stochastic trajectories in continuous time and space. AAMAS 2014: 1109-1116 - [c54]Sarvapali D. Ramchurn, Feng Wu, Wenchao Jiang, Joel E. Fischer, Steven Reece, Chris Greenhalgh, Tom Rodden, Nicholas R. Jennings, Stephen J. Roberts:
AtomicOrchid: human-agent collectives to the rescue. AAMAS 2014: 1693-1694 - [c53]Tom Gunter, Michael A. Osborne, Roman Garnett, Philipp Hennig, Stephen J. Roberts:
Sampling for Inference in Probabilistic Models with Fast Bayesian Quadrature. NIPS 2014: 2789-2797 - [c52]Tom Gunter, Chris M. Lloyd, Michael A. Osborne, Stephen J. Roberts:
Efficient Bayesian Nonparametric Modelling of Structured Point Processes. UAI 2014: 310-319 - [i4]Jan-Peter Calliess, Michael A. Osborne, Stephen J. Roberts:
Conservative collision prediction and avoidance for stochastic trajectories in continuous time and space. CoRR abs/1402.4157 (2014) - [i3]Nabeel Gillani, Rebecca Eynon, Michael A. Osborne, Isis Hjorth, Stephen J. Roberts:
Communication Communities in MOOCs. CoRR abs/1403.4640 (2014) - 2013
- [c51]Sarvapali D. Ramchurn, Michael A. Osborne, Oliver Parson, Talal Rahwan, Sasan Maleki, Steven Reece, Trung Dong Huynh, Muddasser Alam, Joel E. Fischer, Tom Rodden, Luc Moreau, Stephen J. Roberts:
AgentSwitch: towards smart energy tariff selection. AAMAS 2013: 981-988 - [c50]Sarvapali D. Ramchurn, Michael A. Osborne, Oliver Parson, Talal Rahwan, Sasan Maleki, Steven Reece, Trung Dong Huynh, Muddasser Alam, Joel E. Fischer, Tom Rodden, Luc Moreau, Stephen J. Roberts:
AgentSwitch: towards smart energy tariff selection. AAMAS 2013: 1401-1402 - [c49]Trung Dong Huynh, Mark Ebden, Matteo Venanzi, Sarvapali D. Ramchurn, Stephen J. Roberts, Luc Moreau:
Interpretation of Crowdsourced Activities Using Provenance Network Analysis. HCOMP 2013: 78-85 - [c48]Ioannis Psorakis, Iead Rezek, Zach Frankel, Stephen J. Roberts:
Discovering Latent Association Structure via Bayesian one-mode Projection of Temporal Bipartite Graphs. MLDM Posters 2013: 34-38 - [c47]Jan-P. Calliess, Stephen J. Roberts:
Multi-Agent Planning with Mixed-Integer Programming and Adaptive Interaction Constraint Generation (Extended Abstract). SOCS 2013: 207-208 - [p3]Edwin Simpson, Stephen J. Roberts, Ioannis Psorakis, Arfon M. Smith:
Dynamic Bayesian Combination of Multiple Imperfect Classifiers. Decision Making and Imperfection 2013: 1-35 - [i2]Jan-Peter Calliess, Antonis Papachristodoulou, Stephen J. Roberts:
Stochastic processes and feedback-linearisation for online identification and Bayesian adaptive control of fully-actuated mechanical systems. CoRR abs/1311.4468 (2013) - 2012
- [j36]Charles W. Fox, Stephen J. Roberts:
A tutorial on variational Bayesian inference. Artif. Intell. Rev. 38(2): 85-95 (2012) - [j35]Michael A. Osborne, Stephen J. Roberts, Alex Rogers, Nicholas R. Jennings:
Real-time information processing of environmental sensor network data using bayesian gaussian processes. ACM Trans. Sens. Networks 9(1): 1:1-1:32 (2012) - [c46]Jan-Peter Calliess, Michael Alan Osborne, Stephen J. Roberts:
Towards Optimization-Based Multi-Agent Collision-Avoidance Under Continuous Stochastic Dynamics. MAPF@AAAI 2012 - [c45]Mark Smith, Steven Reece, Stephen J. Roberts, Iead Rezek:
Online Maritime Abnormality Detection Using Gaussian Processes and Extreme Value Theory. ICDM 2012: 645-654 - [c44]Mark Ebden, Trung Dong Huynh, Luc Moreau, Sarvapali D. Ramchurn, Stephen J. Roberts:
Network Analysis on Provenance Graphs from a Crowdsourcing Application. IPAW 2012: 168-182 - [c43]Michael A. Osborne, David Duvenaud, Roman Garnett, Carl E. Rasmussen, Stephen J. Roberts, Zoubin Ghahramani:
Active Learning of Model Evidence Using Bayesian Quadrature. NIPS 2012: 46-54 - [c42]Michael A. Osborne, Roman Garnett, Stephen J. Roberts, Christopher Hart, Suzanne Aigrain, Neale Gibson:
Bayesian Quadrature for Ratios. AISTATS 2012: 832-840 - [i1]Ioannis Psorakis, Iead Rezek, Zach Frankel, Stephen J. Roberts:
Bayesian one-mode projection for dynamic bipartite graphs. CoRR abs/1212.2767 (2012) - 2011
- [j34]Mark Ebden, Stephen J. Roberts:
Graph marginalization for rapid assignment in wide-area surveillance. Ad Hoc Networks 9(2): 180-188 (2011) - [j33]Ji Won Yoon, Stephen J. Roberts, Matthew Dyson, John Q. Gan:
Bayesian inference for an adaptive Ordered Probit model: An application to Brain Computer Interfacing. Neural Networks 24(7): 726-734 (2011) - [c41]Steven Reece, Stephen J. Roberts, David Nicholson, Chris M. Lloyd:
Determining intent using hard/soft data and Gaussian process classifiers. FUSION 2011: 1-8 - 2010
- [j32]Seung Min Lee, Stephen J. Roberts:
Sequential Dynamic Classification Using Latent Variable Models. Comput. J. 53(9): 1415-1429 (2010) - [j31]Roman Garnett, Michael A. Osborne, Steven Reece, Alex Rogers, Stephen J. Roberts:
Sequential Bayesian Prediction in the Presence of Changepoints and Faults. Comput. J. 53(9): 1430-1446 (2010) - [j30]D. R. Lowne, Stephen J. Roberts, Roman Garnett:
Sequential non-stationary dynamic classification with sparse feedback. Pattern Recognit. 43(3): 897-905 (2010) - [j29]Ji Won Yoon, Stephen J. Roberts:
Robust Measurement Validation in Target Tracking Using Geometric Structure. IEEE Signal Process. Lett. 17(5): 493-496 (2010) - [j28]Steven Reece, Stephen J. Roberts:
The Near Constant Acceleration Gaussian Process Kernel for Tracking. IEEE Signal Process. Lett. 17(8): 707-710 (2010) - [c40]Michael A. Osborne, Roman Garnett, Stephen J. Roberts:
Active Data Selection for Sensor Networks with Faults and Changepoints. AINA 2010: 533-540 - [c39]Steven Reece, Stephen J. Roberts:
An introduction to Gaussian processes for the Kalman filter expert. FUSION 2010: 1-9 - [c38]Roman Garnett, Michael A. Osborne, Stephen J. Roberts:
Bayesian optimization for sensor set selection. IPSN 2010: 209-219
2000 – 2009
- 2009
- [j27]Lyndsey C. Pickup, David P. Capel, Stephen J. Roberts, Andrew Zisserman:
Bayesian Methods for Image Super-Resolution. Comput. J. 52(1): 101-113 (2009) - [j26]Chun Sing Louis Tsui, John Q. Gan, Stephen J. Roberts:
A self-paced brain-computer interface for controlling a robot simulator: an online event labelling paradigm and an extended Kalman filter based algorithm for online training. Medical Biol. Eng. Comput. 47(3): 257-265 (2009) - [j25]Ji Won Yoon, Stephen J. Roberts, Matthew Dyson, John Q. Gan:
Adaptive classification for Brain Computer Interface systems using Sequential Monte Carlo sampling. Neural Networks 22(9): 1286-1294 (2009) - [c37]Mark Ebden, Stephen J. Roberts:
Graph Marginalization for Rapid Assignment in Wide-Area Surveillance. ADHOCNETS 2009: 691-703 - [c36]Steven Reece, Stephen J. Roberts, Christopher Claxton, David Nicholson:
Multi-sensor fault recovery in the presence of known and unknown fault types. FUSION 2009: 1695-1703 - [c35]Roman Garnett, Michael A. Osborne, Stephen J. Roberts:
Sequential Bayesian prediction in the presence of changepoints. ICML 2009: 345-352 - 2008
- [j24]Iead Rezek, David S. Leslie, Steven Reece, Stephen J. Roberts, Alex Rogers, Rajdeep K. Dash, Nicholas R. Jennings:
On Similarities between Inference in Game Theory and Machine Learning. J. Artif. Intell. Res. 33: 259-283 (2008) - [c34]Mark Ebden, Mark Briers, Stephen J. Roberts:
Decentralized predictive sensor allocation. CDC 2008: 1702-1707 - [c33]Hyoungjoo Lee, Stephen J. Roberts:
On-line novelty detection using the Kalman filter and extreme value theory. ICPR 2008: 1-4 - [c32]Ji Won Yoon, Stephen J. Roberts, Matthew Dyson, John Q. Gan:
Adaptive Classification by Hybrid EKF with Truncated Filtering: Brain Computer Interfacing. IDEAL 2008: 370-377 - [c31]Michael A. Osborne, Stephen J. Roberts, Alex Rogers, Sarvapali D. Ramchurn, Nicholas R. Jennings:
Towards Real-Time Information Processing of Sensor Network Data Using Computationally Efficient Multi-output Gaussian Processes. IPSN 2008: 109-120 - [c30]Ji Won Yoon, Stephen J. Roberts, Matthew Dyson, John Q. Gan:
Sequential Bayesian estimation for adaptive classification. MFI 2008: 601-605 - [c29]Alex Rogers, Mike Osborne, Sarvapali D. Ramchurn, Stephen J. Roberts, Nicholas R. Jennings:
Information Agents for Pervasive Sensor Networks. PerCom 2008: 294-299 - 2007
- [j23]Lyndsey C. Pickup, David P. Capel, Stephen J. Roberts, Andrew Zisserman:
Overcoming Registration Uncertainty in Image Super-Resolution: Maximize or Marginalize? EURASIP J. Adv. Signal Process. 2007 (2007) - [j22]Karen Lees, Stephen J. Roberts, Pari Skamnioti, Sarah J. Gurr:
Gene Microarray Analysis Using Angular Distribution Decomposition. J. Comput. Biol. 14(1): 68-83 (2007) - [c28]Steven Reece, Stephen J. Roberts, Alex Rogers, Nicholas R. Jennings:
A Multi-Dimensional Trust Model for Heterogeneous Contract Observations. AAAI 2007: 128-135 - [c27]Steven Reece, Alex Rogers, Stephen J. Roberts, Nicholas R. Jennings:
Rumours and reputation: evaluating multi-dimensional trust within a decentralised reputation system. AAMAS 2007: 165 - [c26]Ian K. Proudler, Stephen Roberts, Steven Reece, Iead Rezek:
An Iterative Signal Detection Algorithm Based on Bayesian Belief Propagation Ideas. DSP 2007: 355-358 - [c25]Charles W. Fox, Iead Rezek, Stephen J. Roberts:
Drum'n'Bayes: on-Line variational Inference for beat tracking and rhythm Recognition. ICMC 2007 - 2006
- [c24]Alex Rogers, Rajdeep K. Dash, Nicholas R. Jennings, Steven Reece, Stephen J. Roberts:
Computational mechanism design for multi-sensor information fusion. AAMAS 2006: 1463-1464 - [c23]Lyndsey C. Pickup, Stephen J. Roberts, Andrew Zisserman:
Optimizing and Learning for Super-resolution. BMVC 2006: 439-448 - [c22]Alex Rogers, Rajdeep K. Dash, Nick R. Jennings, Steven Reece, Stephen J. Roberts:
Computational Mechanism Design for Information Fusion within Sensor Networks. FUSION 2006: 1-7 - [c21]Max A. Little, Patrick E. McSharry, Irene M. Moroz, Stephen J. Roberts:
Nonlinear, Biophysically-Informed Speech Pathology Detection. ICASSP (2) 2006: 1080-1083 - [c20]Lyndsey C. Pickup, David P. Capel, Stephen J. Roberts, Andrew Zisserman:
Bayesian Image Super-resolution, Continued. NIPS 2006: 1089-1096 - 2005
- [j21]Sach Mukherjee, Stephen J. Roberts:
A Theoretical Analysis of the Selection of Differentially Expressed Genes. J. Bioinform. Comput. Biol. 3(3): 627-644 (2005) - [c19]Sach Mukherjee, Stephen J. Roberts, Mark J. van der Laan:
Data-adaptive test statistics for microarray data. ECCB/JBI 2005: 114 - [c18]Iead Rezek, Stephen J. Roberts, Ellini Siva, R. Conradt:
Depth of anaesthesia assessment with generative polyspectral models. ICMLA 2005 - [c17]Max A. Little, Patrick E. McSharry, Irene M. Moroz, Stephen J. Roberts:
A Simple, Quasi-linear, Discrete Model of Vocal Fold Dynamics. NOLISP 2005: 348-356 - 2004
- [j20]Stephen J. Roberts, Evangelos Roussos, Rizwan Choudrey:
Hierarchy, priors and wavelets: structure and signal modelling using ICA. Signal Process. 84(2): 283-297 (2004) - [j19]Peter Sykacek, Stephen J. Roberts, Maria Stokes:
Adaptive BCI based on variational Bayesian Kalman filtering: an empirical evaluation. IEEE Trans. Biomed. Eng. 51(5): 719-727 (2004) - [c16]Sach Mukherjee, Stephen J. Roberts:
A Theoretical Analysis of Gene Selection. CSB 2004: 131-141 - [c15]Sach Mukherjee, Stephen J. Roberts:
Probabilistic Consistency Analysis for Gene Selection. CSB 2004: 487-488 - [c14]Stephen J. Roberts, Rizwan Choudrey:
Bayesian Independent Component Analysis with Prior Constraints: An Application in Biosignal Analysis. Deterministic and Statistical Methods in Machine Learning 2004: 159-179 - 2003
- [j18]Rizwan Choudrey, Stephen J. Roberts:
Variational Mixture of Bayesian Independent Component Analyzers. Neural Comput. 15(1): 213-252 (2003) - [j17]Stephen J. Roberts, Rizwan Choudrey:
Data decomposition using independent component analysis with prior constraints. Pattern Recognit. 36(8): 1813-1825 (2003) - [j16]S. N. Mukherjee, Stephen J. Roberts, Peter Sykacek, Sarah J. Gurr:
Gene ranking using bootstrapped P-values. SIGKDD Explor. 5(2): 16-22 (2003) - [c13]Iead Rezek, Stephen J. Roberts, Peter Sykacek:
Ensemble Coupled Hidden Markov Models for Joint Characterisation of Dynamic Signals. AISTATS 2003: 233-239 - [c12]Nicholas P. Hughes, Lionel Tarassenko, Stephen J. Roberts:
Markov Models for Automated ECG Interval Analysis. NIPS 2003: 611-618 - [c11]Lyndsey C. Pickup, Stephen J. Roberts, Andrew Zisserman:
A Sampled Texture Prior for Image Super-Resolution. NIPS 2003: 1587-1594 - 2002
- [j15]Jens Rittscher, Andrew Blake, Stephen J. Roberts:
Towards the automatic analysis of complex human body motions. Image Vis. Comput. 20(12): 905-916 (2002) - [j14]Stephen J. Roberts, Will D. Penny:
Variational Bayes for generalized autoregressive models. IEEE Trans. Signal Process. 50(9): 2245-2257 (2002) - [j13]Iead Rezek, Michael Gibbs, Stephen J. Roberts:
Maximum a Posteriori Estimation of Coupled Hidden Markov Models. J. VLSI Signal Process. 32(1-2): 55-66 (2002) - [c10]Iead Rezek, Stephen J. Roberts:
Ensemble hidden Markov models for biosignal analysis. DSP 2002: 387-391 - [c9]Peter Sykacek, Stephen J. Roberts:
Adaptive Classification by Variational Kalman Filtering. NIPS 2002: 737-744 - 2001
- [j12]Stephen J. Roberts, Christopher C. Holmes, Dave Denison:
Minimum-Entropy Data Partitioning Using Reversible Jump Markov Chain Monte Carlo. IEEE Trans. Pattern Anal. Mach. Intell. 23(8): 909-914 (2001) - [c8]Stephen J. Roberts, Christopher C. Holmes, Dave Denison:
Minimum-Entropy Data Clustering Using Reversible Jump Markov Chain Monte Carlo. ICANN 2001: 103-110 - [c7]Stephen J. Roberts, William D. Penny:
Mixtures of Independent Component Analysers. ICANN 2001: 527-534 - [c6]Peter Sykacek, Stephen J. Roberts, Iead Rezek, Arthur Flexer, Georg Dorffner:
A Probabilistic Approach to High-Resolution Sleep Analysis. ICANN 2001: 617-624 - [c5]Peter Sykacek, Stephen J. Roberts:
Bayesian time series classification. NIPS 2001: 937-944 - 2000
- [j11]Stephen J. Roberts, Richard M. Everson, Iead Rezek:
Maximum certainty data partitioning. Pattern Recognit. 33(5): 833-839 (2000) - [j10]Richard M. Everson, Stephen J. Roberts:
Inferring the eigenvalues of covariance matrices from limited, noisy data. IEEE Trans. Signal Process. 48(7): 2083-2091 (2000) - [j9]Richard M. Everson, Stephen J. Roberts:
Blind Source Separation for Non-Stationary Mixing. J. VLSI Signal Process. 26(1-2): 15-23 (2000) - [p2]William D. Penny, Dirk Husmeier, Stephen J. Roberts:
The Bayesian Paradigm: Second Generation Neural Computing. Artificial Neural Networks in Biomedicine 2000: 11-23 - [p1]Richard M. Everson, Stephen J. Roberts:
Independent Components Analysis. Artificial Neural Networks in Biomedicine 2000: 153-168
1990 – 1999
- 1999
- [j8]William D. Penny, Stephen J. Roberts:
Dynamic Models for Nonstationary Signal Segmentation. Comput. Biomed. Res. 32(6): 483-502 (1999) - [j7]Richard M. Everson, Stephen J. Roberts:
Independent Component Analysis: A Flexible Nonlinearity and Decorrelating Manifold Approach. Neural Comput. 11(8): 1957-1983 (1999) - [j6]Dirk Husmeier, William D. Penny, Stephen J. Roberts:
An empirical evaluation of Bayesian sampling with hybrid Monte Carlo for training neural network classifiers. Neural Networks 12(4-5): 677-705 (1999) - [j5]William D. Penny, Stephen J. Roberts:
Bayesian neural networks for classification: how useful is the evidence framework? Neural Networks 12(6): 877-892 (1999) - [c4]William D. Penny, Stephen J. Roberts:
Dynamic logistic regression. IJCNN 1999: 1562-1567 - [c3]William D. Penny, Stephen J. Roberts:
EEG-based communication via dynamic neural network models. IJCNN 1999: 3586-3590 - [c2]Dirk Husmeier, Gillian S. Patton, Myra O. McClure, John R. W. Harris, Stephen J. Roberts:
Neural networks for predicting Kaposi's sarcoma. IJCNN 1999: 3707-3711 - 1998
- [j4]Stephen J. Roberts, Dirk Husmeier, Iead Rezek, William D. Penny:
Bayesian Approaches to Gaussian Mixture Modeling. IEEE Trans. Pattern Anal. Mach. Intell. 20(11): 1133-1142 (1998) - [j3]Iead Rezek, Stephen J. Roberts:
Stochastic complexity measures for physiological signal analysis. IEEE Trans. Biomed. Eng. 45(9): 1186-1191 (1998) - 1997
- [j2]Stephen J. Roberts:
Parametric and non-parametric unsupervised cluster analysis. Pattern Recognit. 30(2): 261-272 (1997) - 1996
- [c1]Stephen J. Roberts:
Scale-space unsupervised cluster analysis. ICPR 1996: 106-110 - 1994
- [j1]Stephen J. Roberts, Lionel Tarassenko:
A Probabilistic Resource Allocating Network for Novelty Detection. Neural Comput. 6(2): 270-284 (1994)
Coauthor Index
Christopher C. Holmes
aka: Chris C. Holmes
aka: Chris C. Holmes
Nicholas R. Jennings
aka: Nick R. Jennings
aka: Nick R. Jennings
Michael A. Osborne
aka: Michael Alan Osborne
aka: Michael Alan Osborne
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