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cs.LG2024
Towards Principled, Practical Policy Gradient for Bandits and Tabular MDPs
Michael Lu, Matin Aghaei, Anant Raj +1
We consider (stochastic) softmax policy gradient (PG) methods for bandits and tabular Markov decision processes (MDPs). While the PG objective is non-concave, recent research has u…
cs.LG2024
From Inverse Optimization to Feasibility to ERM
Saurabh Mishra, Anant Raj, Sharan Vaswani
Inverse optimization involves inferring unknown parameters of an optimization problem from known solutions and is widely used in fields such as transportation, power systems, and h…