1 citations · 1 across the 3 of their papers we have counts for
3 papers
cs.LG2024
Can Implicit Bias Imply Adversarial Robustness?
Hancheng Min, René Vidal
The implicit bias of gradient-based training algorithms has been considered mostly beneficial as it leads to trained networks that often generalize well. However, Frei et al. (2023…
cs.LG2024★ 1 cited
Learning safety critics via a non-contractive binary bellman operator
Agustin Castellano, Hancheng Min, Juan Andrés Bazerque +1
The inability to naturally enforce safety in Reinforcement Learning (RL), with limited failures, is a core challenge impeding its use in real-world applications. One notion of safe…
eess.SY2023
A Frequency Domain Analysis of Slow Coherency in Networked Systems
Hancheng Min, Richard Pates, Enrique Mallada
Network coherence generally refers to the emergence of simple aggregated dynamical behaviours, despite heterogeneity in the dynamics of the subsystems that constitute the network.…