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$\texttt{FedBC}$: Calibrating Global and Local Models via Federated Learning Beyond Consensus



Amrit Singh Bedi , Chen Fan , Alec Koppel , Anit Kumar Sahu , Brian M. Sadler , Furong Huang , Dinesh Manocha


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Achieving Zero Constraint Violation for Constrained Reinforcement Learning via Conservative Natural Policy Gradient Primal-Dual Algorithm



Qinbo Bai , Amrit Singh Bedi , Vaneet Aggarwal


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Dealing with Sparse Rewards in Continuous Control Robotics via Heavy-Tailed Policies



Souradip Chakraborty , Amrit Singh Bedi , Alec Koppel , Pratap Tokekar , Dinesh Manocha


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Posterior Coreset Construction with Kernelized Stein Discrepancy for Model-Based Reinforcement Learning



Souradip Chakraborty , Amrit Singh Bedi , Alec Koppel , Brian M. Sadler , Furong Huang , Pratap Tokekar , Dinesh Manocha


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Distributed Riemannian Optimization with Lazy Communication for Collaborative Geometric Estimation



Yulun Tian , Amrit Singh Bedi , Alec Koppel , Miguel Calvo-Fullana , David M. Rosen , Jonathan P. How

* technical report (17 pages, 3 figures) 

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On the Hidden Biases of Policy Mirror Ascent in Continuous Action Spaces



Amrit Singh Bedi , Souradip Chakraborty , Anjaly Parayil , Brian Sadler , Pratap Tokekar , Alec Koppel


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Projection-Free Algorithm for Stochastic Bi-level Optimization



Zeeshan Akhtar , Amrit Singh Bedi , Srujan Teja Thomdapu , Ketan Rajawat

* 34 Pages 

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Convergence Rates of Average-Reward Multi-agent Reinforcement Learning via Randomized Linear Programming



Alec Koppel , Amrit Singh Bedi , Bhargav Ganguly , Vaneet Aggarwal


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Achieving Zero Constraint Violation for Constrained Reinforcement Learning via Primal-Dual Approach



Qinbo Bai , Amrit Singh Bedi , Mridul Agarwal , Alec Koppel , Vaneet Aggarwal


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Wasserstein-Splitting Gaussian Process Regression for Heterogeneous Online Bayesian Inference



Michael E. Kepler , Alec Koppel , Amrit Singh Bedi , Daniel J. Stilwell


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