21 citations · 149 across the 34 of their papers we have counts for
4 papers · 1 filter
From Eye-blinks to State Construction: Diagnostic Benchmarks for Online Representation Learning
Banafsheh Rafiee, Zaheer Abbas, Sina Ghiassian +4
We present three new diagnostic prediction problems inspired by classical-conditioning experiments to facilitate research in online prediction learning. Experiments in classical co…
Towards a practical measure of interference for reinforcement learning
Vincent Liu, Adam White, Hengshuai Yao +1
Catastrophic interference is common in many network-based learning systems, and many proposals exist for mitigating it. But, before we overcome interference we must understand it b…
Gradient Temporal-Difference Learning with Regularized Corrections
Sina Ghiassian, Andrew Patterson, Shivam Garg +3
It is still common to use Q-learning and temporal difference (TD) learning-even though they have divergence issues and sound Gradient TD alternatives exist-because divergence seems…
Improving Performance in Reinforcement Learning by Breaking Generalization in Neural Networks
Sina Ghiassian, Banafsheh Rafiee, Yat Long Lo +1
Reinforcement learning systems require good representations to work well. For decades practical success in reinforcement learning was limited to small domains. Deep reinforcement l…