3 papers
cs.LG2022
Learn to Match with No Regret: Reinforcement Learning in Markov Matching Markets
Yifei Min, Tianhao Wang, Ruitu Xu +3
We study a Markov matching market involving a planner and a set of strategic agents on the two sides of the market. At each step, the agents are presented with a dynamical context,…
cs.LG2020
The Curious Case of Adversarially Robust Models: More Data Can Help, Double Descend, or Hurt Generalization
Yifei Min, Lin Chen, Amin Karbasi
Adversarial training has shown its ability in producing models that are robust to perturbations on the input data, but usually at the expense of decrease in the standard accuracy.…
cs.LG2020
More Data Can Expand the Generalization Gap Between Adversarially Robust and Standard Models
Lin Chen, Yifei Min, Mingrui Zhang +1
Despite remarkable success in practice, modern machine learning models have been found to be susceptible to adversarial attacks that make human-imperceptible perturbations to the d…