We present a model-free reinforcement learning method for partially observable Markov decision problems. Our method estimates a likelihood gradient by sampling directly in paramet...
—Many important audio coding applications, such as streaming and playback of stored audio, involve offline compression. In such scenarios, encoding delays no longer represent a ...
Designing efficient bidding strategies for sequential auctions remains an important, open problem area in agent-mediated electronic markets. In existing literature, a variety of bi...
In this paper, we study the decision making process involved in the five year lifecycle of a Bluetooth software product produced by a large, multi-national test and measurement fi...
Recently, a number of researchers have proposed spectral algorithms for learning models of dynamical systems—for example, Hidden Markov Models (HMMs), Partially Observable Marko...