3 citations · 10 across the 24 of their papers we have counts for
8 papers · 1 filter
Optimism Without Regularization: Constant Regret in Zero-Sum Games
John Lazarsfeld, Georgios Piliouras, Ryann Sim +1
This paper studies the optimistic variant of Fictitious Play for learning in two-player zero-sum games. While it is known that Optimistic FTRL -- a regularized algorithm with a bou…
Best of Both Worlds: Regret Minimization versus Minimax Play
Adrian Müller, Jon Schneider, Stratis Skoulakis +2
In this paper, we investigate the existence of online learning algorithms with bandit feedback that simultaneously guarantee regret compared to a given comparator strategy,…
Imitation Learning in Discounted Linear MDPs without exploration assumptions
Luca Viano, Stratis Skoulakis, Volkan Cevher
We present a new algorithm for imitation learning in infinite horizon linear MDPs dubbed ILARL which greatly improves the bound on the number of trajectories that the learner needs…
Maximum Independent Set: Self-Training through Dynamic Programming
Lorenzo Brusca, Lars C. P. M. Quaedvlieg, Stratis Skoulakis +2
This work presents a graph neural network (GNN) framework for solving the maximum independent set (MIS) problem, inspired by dynamic programming (DP). Specifically, given a graph,…
STay-ON-the-Ridge: Guaranteed Convergence to Local Minimax Equilibrium in Nonconvex-Nonconcave Games
Constantinos Daskalakis, Noah Golowich, Stratis Skoulakis +1
Min-max optimization problems involving nonconvex-nonconcave objectives have found important applications in adversarial training and other multi-agent learning settings. Yet, no k…
Efficient Online Learning for Dynamic k-Clustering
Dimitris Fotakis, Georgios Piliouras, Stratis Skoulakis
We study dynamic clustering problems from the perspective of online learning. We consider an online learning problem, called \textit{Dynamic -Clustering}, in which centers a…
Efficient Online Learning of Optimal Rankings: Dimensionality Reduction via Gradient Descent
Dimitris Fotakis, Thanasis Lianeas, Georgios Piliouras +1
We consider a natural model of online preference aggregation, where sets of preferred items along with a demand for items in each , appear online…
Convergence to Second-Order Stationarity for Non-negative Matrix Factorization: Provably and Concurrently
Ioannis Panageas, Stratis Skoulakis, Antonios Varvitsiotis +1
Non-negative matrix factorization (NMF) is a fundamental non-convex optimization problem with numerous applications in Machine Learning (music analysis, document clustering, speech…