We present an algorithm called Optimistic Linear Programming (OLP) for learning to optimize average reward in an irreducible but otherwise unknown Markov decision process (MDP). O...
Program-counter-based (PC-based) prediction techniques have been shown to be highly effective and are widely used in computer architecture design. In this paper, we explore the op...
Verification of multi-threaded C++ programs poses three major challenges: the large number of states, states with huge sizes, and time intensive expansions of states. This paper p...
We explore an application to the game of Go of a reinforcement learning approach based on a linear evaluation function and large numbers of binary features. This strategy has prov...
Many structured prediction tasks involve complex models where inference is computationally intractable, but where it can be well approximated using a linear programming relaxation...
Ofer Meshi, David Sontag, Tommi Jaakkola, Amir Glo...