9 citations · 20 across the 10 of their papers we have counts for
4 papers · 1 filter
Learning Pessimism for Robust and Efficient Off-Policy Reinforcement Learning
Edoardo Cetin, Oya Celiktutan
Off-policy deep reinforcement learning algorithms commonly compensate for overestimation bias during temporal-difference learning by utilizing pessimistic estimates of the expected…
Learning Routines for Effective Off-Policy Reinforcement Learning
Edoardo Cetin, Oya Celiktutan
The performance of reinforcement learning depends upon designing an appropriate action space, where the effect of each action is measurable, yet, granular enough to permit flexible…
IB-DRR: Incremental Learning with Information-Back Discrete Representation Replay
Jian Jiang, Edoardo Cetin, Oya Celiktutan
Incremental learning aims to enable machine learning models to continuously acquire new knowledge given new classes, while maintaining the knowledge already learned for old classes…
Domain-Robust Visual Imitation Learning with Mutual Information Constraints
Edoardo Cetin, Oya Celiktutan
Human beings are able to understand objectives and learn by simply observing others perform a task. Imitation learning methods aim to replicate such capabilities, however, they gen…