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UAI
1998
13 years 10 months ago
Learning the Structure of Dynamic Probabilistic Networks
Dynamic probabilistic networks are a compact representation of complex stochastic processes. In this paper we examine how to learn the structure of a DPN from data. We extend stru...
Nir Friedman, Kevin P. Murphy, Stuart J. Russell
AROBOTS
1998
113views more  AROBOTS 1998»
13 years 9 months ago
Grounding Mundane Inference in Perception
We describe a uniform technique for representing both sensory data and the attentional state of an agent using a subset of modal logic with indexicals. The resulting representation...
Ian Horswill
TNN
1998
99views more  TNN 1998»
13 years 9 months ago
Comments on local minima free conditions in multilayer perceptrons
—In this letter we point out that multilayer neural networks (MLP’s) with either sigmoidal units or radial basis functions can be given a canonical form with positive interunit...
Marco Gori, Ah Chung Tsoi
NIPS
1998
13 years 10 months ago
Example-Based Image Synthesis of Articulated Figures
We present a method for learning complex appearance mappings, such as occur with images of articulated objects. Traditional interpolation networks fail on this case since appearan...
Trevor Darrell
ICMAS
1998
13 years 10 months ago
A Market Protocol for Decentralized Task Allocation
We present a decentralized, asynchronous market protocol for allocating and scheduling tasks among agents that contend for scarce resources, constrained by a hierarchical task dep...
William E. Walsh, Michael P. Wellman