L1 regularization is effective for feature selection, but the resulting optimization is challenging due to the non-differentiability of the 1-norm. In this paper we compare state...
Combinatorial allocation problems require allocating items to players in a way that maximizes the total utility. Two such problems received attention recently, and were addressed ...
—TD learning and its refinements are powerful tools for approximating the solution to dynamic programming problems. However, the techniques provide the approximate solution only...
Wei Chen, Dayu Huang, Ankur A. Kulkarni, Jayakrish...
Abstract. In this work, we address the problem of transient and steadystate analysis of a stochastic Petri net which includes non Markovian distributions with a finite support but ...
Abstract. In this paper we present a heuristic based on dynamic approximations for improving the well-known Schnorr-Euchner lattice basis reduction algorithm. In particular, the ne...