7 citations · 9 across the 4 of their papers we have counts for
7 papers
Regret Pruning for Learning Equilibria in Simulation-Based Games
Bhaskar Mishra, Cyrus Cousins, Amy Greenwald
In recent years, empirical game-theoretic analysis (EGTA) has emerged as a powerful tool for analyzing games in which an exact specification of the utilities is unavailable. Instea…
An Axiomatic Theory of Provably-Fair Welfare-Centric Machine Learning
Cyrus Cousins
We address an inherent difficulty in welfare-theoretic fair machine learning by proposing an equivalently axiomatically-justified alternative and studying the resulting computation…
Learning Competitive Equilibria in Noisy Combinatorial Markets
Enrique Areyan Viqueira, Cyrus Cousins, Amy Greenwald
We present a methodology to robustly estimate the competitive equilibria (CE) of combinatorial markets under the assumption that buyers do not know their precise valuations for bun…
Making mean-estimation more efficient using an MCMC trace variance approach: DynaMITE
Cyrus Cousins, Shahrzad Haddadan, Eli Upfal
We introduce a novel statistical measure for MCMC-mean estimation, the inter-trace variance , which depends on a Markov chain and a fu…
MCRapper: Monte-Carlo Rademacher Averages for Poset Families and Approximate Pattern Mining
Leonardo Pellegrina, Cyrus Cousins, Fabio Vandin +1
We present MCRapper, an algorithm for efficient computation of Monte-Carlo Empirical Rademacher Averages (MCERA) for families of functions exhibiting poset (e.g., lattice) structur…
Learning Equilibria of Simulation-Based Games
Enrique Areyan Viqueira, Cyrus Cousins, Eli Upfal +1
We tackle a fundamental problem in empirical game-theoretic analysis (EGTA), that of learning equilibria of simulation-based games. Such games cannot be described in analytical for…