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NIPS
1998
15 years 6 months ago
Approximate Learning of Dynamic Models
Inference is a key component in learning probabilistic models from partially observable data. When learning temporal models, each of the many inference phases requires a complete ...
Xavier Boyen, Daphne Koller
EUROPDS
1997
15 years 6 months ago
A Combined Virtual Shared Memory and Network which Schedules
In this paper, we follow a new path to arrive at the idea of a COMA — a Cache Only Memory Architecture. We show how the evolution of another architecture (ADARC) leads quite nat...
Ronald Moore, Bernd Klauer, Klaus Waldschmidt
157
Voted
IJCAI
1997
15 years 6 months ago
Learning Topological Maps with Weak Local Odometric Information
cal maps provide a useful abstraction for robotic navigation and planning. Although stochastic mapscan theoreticallybe learned using the Baum-Welch algorithm,without strong prior ...
Hagit Shatkay, Leslie Pack Kaelbling
113
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EACL
1989
ACL Anthology
15 years 6 months ago
User studies and the design of Natural Language Systems
This paper presents a critical discussion of the various approaches that have been used in the evaluation of Natural Language systems. We conclude that previous approaches have ne...
Steve Whittaker, Phil Stenton
USENIX
1990
15 years 6 months ago
A New Design for Distributed Systems: The Remote Memory Model
This paper describes a new model for constructing distributed systems called the Remote Memory Model. The remote memory model consists of several client machines, one or more dedi...
Douglas Comer, Jim Griffioen
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