596 citations · 1.7k across the 25 of their papers we have counts for
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cs.LG2019
A Generalized Algorithm for Multi-Objective Reinforcement Learning and Policy Adaptation
Runzhe Yang, Xingyuan Sun, Karthik Narasimhan
We introduce a new algorithm for multi-objective reinforcement learning (MORL) with linear preferences, with the goal of enabling few-shot adaptation to new tasks. In MORL, the aim…
cs.CL2019★ 13 cited
Calibration, Entropy Rates, and Memory in Language Models
Mark Braverman, Xinyi Chen, Sham M. Kakade +3
Building accurate language models that capture meaningful long-term dependencies is a core challenge in natural language processing. Towards this end, we present a calibration-base…
cs.LG2019★ 10 cited
Task-Agnostic Dynamics Priors for Deep Reinforcement Learning
Yilun Du, Karthik Narasimhan
While model-based deep reinforcement learning (RL) holds great promise for sample efficiency and generalization, learning an accurate dynamics model is often challenging and requir…