We present a set of algorithms that enable us to translate natural language sentences by exploiting both a translation memory and a statistical-based translation model. Our result...
Causality constraints of random discrete simulation make parallel and distributed processing difficult. Methods of applying reconfigurable logic to implement and accelerate simula...
We present an overview of Candide, a system for automatic translation of French text to English text. Candide uses methods of information theory and statistics to develop a probab...
Adam L. Berger, Peter F. Brown, Stephen Della Piet...
Improving the sample efficiency of reinforcement learning algorithms to scale up to larger and more realistic domains is a current research challenge in machine learning. Model-ba...
Abstract. In contrast to the standard inductive inference setting of predictive machine learning, in real world learning problems often the test instances are already available at ...