We study the quality of LP-based approximation methods for pure combinatorial problems. We found that the quality of the LPrelaxation is a direct function of the underlying constra...
Abstract-- The need for efficient computation of approximate global state lies at the heart of a wide range of problems in distributed systems. Examples include routing in the Inte...
Approximate string matching is an important paradigm in domains ranging from speech recognition to information retrieval and molecular biology. In this paper, we introduce a new f...
For nearest neighbor search, a user queries a server for nearby points of interest (POIs) with his/her location information. Our aim is to protect the user’s sensitive informatio...
This paper describes a computationally feasible approximation to the AIXI agent, a universal reinforcement learning agent for arbitrary environments. AIXI is scaled down in two ke...
Joel Veness, Kee Siong Ng, Marcus Hutter, William ...