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» Learning Generative Models with the Up-Propagation Algorithm
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CP
2006
Springer
13 years 11 months ago
A New Algorithm for Sampling CSP Solutions Uniformly at Random
The paper presents a method for generating solutions of a constraint satisfaction problem (CSP) uniformly at random. The main idea is to express the CSP as a factored probability d...
Vibhav Gogate, Rina Dechter
CLOR
2006
13 years 11 months ago
Sequential Learning of Layered Models from Video
Abstract. A popular framework for the interpretation of image sequences is the layers or sprite model, see e.g. [1], [2]. Jojic and Frey [3] provide a generative probabilistic mode...
Michalis K. Titsias, Christopher K. I. Williams
ATAL
2008
Springer
13 years 9 months ago
MB-AIM-FSI: a model based framework for exploiting gradient ascent multiagent learners in strategic interactions
Future agent applications will increasingly represent human users autonomously or semi-autonomously in strategic interactions with similar entities. Hence, there is a growing need...
Doran Chakraborty, Sandip Sen
ICML
2009
IEEE
14 years 8 months ago
Herding dynamical weights to learn
A new "herding" algorithm is proposed which directly converts observed moments into a sequence of pseudo-samples. The pseudosamples respect the moment constraints and ma...
Max Welling
KDD
2009
ACM
224views Data Mining» more  KDD 2009»
14 years 8 days ago
Issues in evaluation of stream learning algorithms
Learning from data streams is a research area of increasing importance. Nowadays, several stream learning algorithms have been developed. Most of them learn decision models that c...
João Gama, Raquel Sebastião, Pedro P...