6 papers
One Size Does Not Fit All: Curvature-Aware Adaptive Perturbation for SAM
Alessia Rossi, Felipe Campelo, Gabriel L. Oliveira
Poor generalisation in deep neural networks is frequently associated with convergence to sharp minima. Sharpness-Aware Minimisation (SAM) improves generalisation of deep neural net…
A Memory Efficient Unified Algorithm for Online Learning of Linear Dynamical Systems
Yuval Ran-Milo, Angelos Assos, Elad Hazan
Motivated by the challenge of stabilizing a general unknown linear dynamical system (LDS) from observations, we study the natural prerequisite of online prediction. Our goal is to…
Alternates, Assemble! Selecting Optimal Alternates for Citizens' Assemblies
Angelos Assos, Carmel Baharav, Bailey Flanigan +1
Citizens' assemblies are an increasingly influential form of deliberative democracy, where randomly selected people discuss policy questions. The legitimacy of these assemblies hin…
Computational Intractability of Strategizing against Online Learners
Angelos Assos, Yuval Dagan, Nived Rajaraman
Online learning algorithms are widely used in strategic multi-agent settings, including repeated auctions, contract design, and pricing competitions, where agents adapt their strat…
Maximizing utility in multi-agent environments by anticipating the behavior of other learners
Angelos Assos, Yuval Dagan, Constantinos Daskalakis
Learning algorithms are often used to make decisions in sequential decision-making environments. In multi-agent settings, the decisions of each agent can affect the utilities/losse…
Online Learning and Solving Infinite Games with an ERM Oracle
Angelos Assos, Idan Attias, Yuval Dagan +2
While ERM suffices to attain near-optimal generalization error in the stochastic learning setting, this is not known to be the case in the online learning setting, where algorithms…