Andrew Patterson

Joined

December 2017

Names

Andrew Patterson

Emails

****@indiana.edu (Confirmed)

,

****@ualberta.ca (Confirmed)

Personal Links

Career & Education History

PhD student

University of Alberta (ualberta.ca)

2018 – 2023

Advisors, Relations & Conflicts

PhD Advisor

2018 – 2023

Coauthor

2018 – 2023

Expertise

Reinforcement Learning

Present

Off-policy learning

Present

Optimization

Present

Dictionary learning

Present

Publications

The Cell Must Go On: Agar.io for Continual Reinforcement Learning
Mohamed Ayman Mohamed, Kateryna Nekhomiazh, Vedant Vyas, Marcos Menon Jose, Andrew Patterson, Marlos C. Machado
- Submitted to ICLR 2026
- Readers: Everyone
Deep Reinforcement Learning with Gradient Eligibility Traces
Esraa Elelimy, Brett Daley, Andrew Patterson, Marlos C. Machado, Adam White, Martha White
- RLC 2025
- Readers: Everyone
Cross-environment Hyperparameter Tuning for Reinforcement Learning
Andrew Patterson, Samuel Neumann, Raksha Kumaraswamy, Martha White, Adam White
- RLC 2024
- Readers: Everyone
Investigating the Interplay of Prioritized Replay and Generalization
Parham Mohammad Panahi, Andrew Patterson, Martha White, Adam White
- RLC 2024
- Readers: Everyone
A Gradient Critic for Policy Gradient Estimation
Samuele Tosatto, Andrew Patterson, Martha White, A. Rupam Mahmood
- Published: 20 Jul 2023, Last Modified: 29 Aug 2023
- EWRL16
- Readers: Everyone
When is Offline Hyperparameter Selection Feasible for Reinforcement Learning?
Vincent Liu, Prabhat Nagarajan, Andrew Patterson, Martha White
- Published: 01 Feb 2023, Last Modified: 13 Feb 2023
- Submitted to ICLR 2023
- Readers: Everyone
Robust Losses for Learning Value Functions
Andrew Patterson, Victor Liao, Martha White
- Published: 28 Jan 2022, Last Modified: 13 Feb 2023
- ICLR 2022 Submitted
- Readers: Everyone
The Cross-environment Hyperparameter Setting Benchmark for Reinforcement Learning
Andrew Patterson, Samuel Neumann, Raksha Kumaraswamy, Martha White, Adam M White
- 07 Jun 2021 (modified: 24 May 2023)
- Submitted to NeurIPS 2021 Datasets and Benchmarks Track (Round 1)
- Readers: Everyone
Learning Macroscopic Brain Connectomes via Group-Sparse Factorization.
Farzane Aminmansour, Andrew Patterson, Lei Le, Yisu Peng, Daniel Mitchell, Franco Pestilli, Cesar F. Caiafa, Russell Greiner, Martha White
- 2019 (modified: 09 Nov 2022)
- NeurIPS2019
- Readers: Everyone
Supervised autoencoders: Improving generalization performance with unsupervised regularizers
Lei Le, Andrew Patterson, Martha White
- 2018 (modified: 11 Nov 2022)
- NeurIPS 2018
- Readers: Everyone

View all 13 publications

Co-Authors

View all 29 co-authors