22 citations · 28 across the 3 of their papers we have counts for
3 papers
Transfer Reinforcement Learning for Differing Action Spaces via Q-Network Representations
Nathan Beck, Abhiramon Rajasekharan, Hieu Tran
Transfer learning approaches in reinforcement learning aim to assist agents in learning their target domains by leveraging the knowledge learned from other agents that have been tr…
SIMILAR: Submodular Information Measures Based Active Learning In Realistic Scenarios
Suraj Kothawade, Nathan Beck, Krishnateja Killamsetty +1
Active learning has proven to be useful for minimizing labeling costs by selecting the most informative samples. However, existing active learning methods do not work well in reali…
Effective Evaluation of Deep Active Learning on Image Classification Tasks
Nathan Beck, Durga Sivasubramanian, Apurva Dani +2
With the goal of making deep learning more label-efficient, a growing number of papers have been studying active learning (AL) for deep models. However, there are a number of issue…