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» Variational methods for Reinforcement Learning
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UAI
2008
13 years 9 months ago
Knowledge Combination in Graphical Multiagent Models
A graphical multiagent model (GMM) represents a joint distribution over the behavior of a set of agents. One source of knowledge aboutagents'behaviormaycomefromgametheoretic ...
Quang Duong, Michael P. Wellman, Satinder P. Singh
ICMCS
2007
IEEE
180views Multimedia» more  ICMCS 2007»
14 years 2 months ago
Discrete Regularization for Perceptual Image Segmentation via Semi-Supervised Learning and Optimal Control
In this paper, we present a regularization approach on discrete graph spaces for perceptual image segmentation via semisupervised learning. In this approach, first, a spectral cl...
Hongwei Zheng, Olaf Hellwich
PG
2003
IEEE
14 years 1 months ago
Neural Meshes: Statistical Learning Based on Normals
We present a method for the adaptive reconstruction of a surface directly from an unorganized point cloud. The algorithm is based on an incrementally expanding Neural Network and ...
Won-Ki Jeong, Ioannis P. Ivrissimtzis, Hans-Peter ...
ICANN
2001
Springer
14 years 8 days ago
Incremental Support Vector Machine Learning: A Local Approach
Abstract. In this paper, we propose and study a new on-line algorithm for learning a SVM based on Radial Basis Function Kernel: Local Incremental Learning of SVM or LISVM. Our meth...
Liva Ralaivola, Florence d'Alché-Buc
COLING
1996
13 years 9 months ago
Learning dialog act processing
In this paper we describe a new approach for learning dialog act processing. In this approach we integrate a symbolic semantic segmentation parse,: with a learning dialog act netw...
Stefan Wermter, Matthias Lochel