3 papers
cs.LG2026
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…
cs.LG2025
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…
cs.GT2025
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…