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» Learning Useful Horn Approximations
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ICML
2004
IEEE
14 years 10 months ago
Approximate inference by Markov chains on union spaces
A standard method for approximating averages in probabilistic models is to construct a Markov chain in the product space of the random variables with the desired equilibrium distr...
Max Welling, Michal Rosen-Zvi, Yee Whye Teh
FOCS
2008
IEEE
14 years 4 months ago
Submodular Approximation: Sampling-based Algorithms and Lower Bounds
We introduce several generalizations of classical computer science problems obtained by replacing simpler objective functions with general submodular functions. The new problems i...
Zoya Svitkina, Lisa Fleischer
SIGGRAPH
1998
ACM
14 years 2 months ago
Progressive Forest Split Compression
In this paper we introduce the Progressive Forest Split (PFS) representation, a new adaptive refinement scheme for storing and transmitting manifold triangular meshes in progress...
Gabriel Taubin, André Guéziec, Willi...
TNN
2008
119views more  TNN 2008»
13 years 9 months ago
Selecting Useful Groups of Features in a Connectionist Framework
Abstract--Suppose for a given classification or function approximation (FA) problem data are collected using sensors. From the output of the th sensor, features are extracted, ther...
Debrup Chakraborty, Nikhil R. Pal
ICML
2007
IEEE
14 years 10 months ago
Learning state-action basis functions for hierarchical MDPs
This paper introduces a new approach to actionvalue function approximation by learning basis functions from a spectral decomposition of the state-action manifold. This paper exten...
Sarah Osentoski, Sridhar Mahadevan