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» Variational methods for Reinforcement Learning
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UAI
2008
15 years 7 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»
16 years 14 days 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
15 years 11 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
15 years 10 months 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
15 years 7 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