Publications

Published papers

Investigating Action Encodings in Recurrent Neural Networks in Reinforcement Learning. Matthew Schlegel, Volodmyr Tkachuk, Adam White, Martha White. Transactions on Machine Learning Research, 2022.

Structural Credit Assignment in Neural Networks using Reinforcement Learning. Dhawal Gupta, Gabor Mihucz, Matthew Schlegel, James Kostas, Philip S Thomas, Martha White. Advances in Neural Information Processing Systems, 2021.

General Value Function Networks. Matthew Schlegel, Andrew Jacobsen, Zaheer Abbas, Andrew Patterson, Adam White, Martha White. Journal of Artificial Intelligence Research, 2021.

Continual Auxiliary Task Learning. Matthew McLeod, Chunlok Lo, Matthew Schlegel, Andrew Jacobsen, Raksha Kumaraswamy, Martha White, Adam White. Advances in Neural Information Processing Systems, 2021.

Meta-descent for Online, Continual Prediction. Andrew Jacobsen, Matthew Schlegel, Cameron Linke, Thomas Degris, Adam White, Martha White. AAAI Conference on Artificial Intelligence, 2019.

Importance Resampling for Off-policy Prediction. Matthew Schlegel, Wesley Chung, Daniel Graves, Jian Qian, Martha White. Advances in Neural Information Processing Systems 32, 2019.

Context-dependent upper-confidence bounds for directed exploration. Raksha Kumaraswamy, Matthew Schlegel, Adam White, Martha White. Advances in Neural Information Processing Systems, 2018.

Adapting kernel representations online using submodular maximization. Matthew Schlegel, Yangchen Pan, Jiecao Chen, Martha White. Proceedings of the 34th International Conference on Machine Learning-Volume 70, 2017.

Other papers

Predictions predicting predictions. Matthew Schlegel, Martha White. The Multi-disciplinary Conference on Reinforcement Learning and Decision Making, 2022.

A Baseline of Discovery for General Value Function Networks under Partial Observability. Matthew Schlegel, Adam White, Martha White. NeurIPS Workshop on Reinforcement Learning under Partial Observability, 2018.

Stable predictive representations with general value functions for continual learning. Matthew Schlegel, Adam White, Martha White. NeurIPS Workshop on Continual Learning and Deep Networks, 2017.