This paper investigates a new learning formulation called dynamic group sparsity. It is a natural extension of the standard sparsity concept in compressive sensing, and is motivat...
Can learning algorithms find a Nash equilibrium? This is a natural question for several reasons. Learning algorithms resemble the behavior of players in many naturally arising gam...
Constantinos Daskalakis, Rafael Frongillo, Christo...
Abstract A dynamic programming algorithm for constructing optimal dyadic decision trees was recently introduced, analyzed, and shown to be very effective for low dimensional data ...
In many dynamic matching applications—especially high-stakes ones—the competitive ratios of prior-free online algorithms are unacceptably poor. The algorithm should take distr...
John P. Dickerson, Ariel D. Procaccia, Tuomas Sand...
— The population-based incremental learning (PBIL) algorithm is a combination of evolutionary optimization and competitive learning. Recently, the PBIL algorithm has been applied...