Adapting Kernel Representations Online Using Submodular Maximization. - Matthew Schlegel; Yangchen Pan; Jiecao Chen; Martha White (ICML, 2017)

Context-dependent upper-confidence bounds for directed exploration. - Raksha Kumaraswamy; Matthew Schlegel; Adam White 001; Martha White (NeurIPS, 2018)

General Value Function Networks. - Matthew Schlegel; Adam White 001; Andrew Patterson; Martha White (CoRR, 2018)

Meta-Descent for Online, Continual Prediction. - Andrew Jacobsen; Matthew Schlegel; Cameron Linke; Thomas Degris; Adam White 001; Martha White (AAAI, 2019)

Importance Resampling for Off-policy Prediction. - Matthew Schlegel; Wesley Chung; Daniel Graves; Jian Qian; Martha White (NeurIPS, 2019)

Structural Credit Assignment in Neural Networks using Reinforcement Learning. - Dhawal Gupta; Gabor Mihucz; Matthew Schlegel; James E. Kostas; Philip S. Thomas; Martha White (NeurIPS, 2021)

Continual Auxiliary Task Learning. - Matthew McLeod; Chunlok Lo; Matthew Schlegel; Andrew Jacobsen; Raksha Kumaraswamy; Martha White; Adam White 001 (NeurIPS, 2021)

General Value Function Networks. - Matthew Schlegel; Andrew Jacobsen; Zaheer Abbas; Andrew Patterson; Adam White 001; Martha White (J. Artif. Intell. Res., 2021)

General Munchausen Reinforcement Learning with Tsallis Kullback-Leibler Divergence. - Lingwei Zhu; Zheng Chen 012; Matthew Schlegel; Martha White (NeurIPS, 2023)

Investigating Action Encodings in Recurrent Neural Networks in Reinforcement Learning. - Matthew Schlegel; Volodymyr Tkachuk; Adam M. White; Martha White (Trans. Mach. Learn. Res., 2023)

Offline Reinforcement Learning via Tsallis Regularization. - Lingwei Zhu; Matthew Schlegel; Han Wang; Martha White (Trans. Mach. Learn. Res., 2024)

Human-like Bots for Tactical Shooters Using Compute-Efficient Sensors. - Niels Justesen; Maria Kaselimi; Sam Snodgrass; Miruna Vozaru; Matthew Schlegel; Jonas Wingren; Gabriella A. B. Barros; Tobias Mahlmann; Shyam Sudhakaran; Wesley Kerr; Albert Wang; Christoffer Holmgård; et al. (CoRR, 2025)