15 citations · 22 across the 13 of their papers we have counts for
4 papers · 1 filter
Reinforcement Learning with Almost Sure Constraints
Agustin Castellano, Hancheng Min, Juan Bazerque +1
In this work we address the problem of finding feasible policies for Constrained Markov Decision Processes under probability one constraints. We argue that stationary policies are…
Learning to Act Safely with Limited Exposure and Almost Sure Certainty
Agustin Castellano, Hancheng Min, Juan Bazerque +1
This paper puts forward the concept that learning to take safe actions in unknown environments, even with probability one guarantees, can be achieved without the need for an unboun…
Convergence and Implicit Bias of Gradient Flow on Overparametrized Linear Networks
Hancheng Min, Salma Tarmoun, Rene Vidal +1
Neural networks trained via gradient descent with random initialization and without any regularization enjoy good generalization performance in practice despite being highly overpa…
Coherence and Concentration in Tightly-Connected Networks
Hancheng Min, Richard Pates, Enrique Mallada
The ability to achieve coordinated behavior -- engineered or emergent -- on networked systems has attracted widespread interest over several fields. This interest has led to remark…