In normal scenarios, computer scientists often consider the number of states in a game to capture the difficulty of learning an equilibrium. However, players do not see games in ...
We study the common problem of approximating a target matrix with a matrix of lower rank. We provide a simple and efficient (EM) algorithm for solving weighted low-rank approximat...
— This paper applies a recently developed neural network called plausible neural network (PNN) to function approximation. Instead of using error correction, PNN estimates the mut...
Markov Random Fields (MRF's) can be used for a wide variety of vision problems. In this paper we focus on MRF's with two-valued clique potentials, which form a generaliz...
Classical rate-distortion theory requires knowledge of an elusive source distribution. Instead, we analyze rate-distortion properties of individual objects using the recently devel...