Publications

In Progress

General Value Function Networks. Matthew Schlegel, Andrew Jacobsen, Muhammad Zaheer, Andrew Patterson, Adam White, Martha White . arXiv preprint arXiv:1807.06763, 2020.

Published papers

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

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.