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» Sublinear Optimization for Machine Learning
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149
Voted
ML
2007
ACM
192views Machine Learning» more  ML 2007»
15 years 1 months ago
Annealing stochastic approximation Monte Carlo algorithm for neural network training
We propose a general-purpose stochastic optimization algorithm, the so-called annealing stochastic approximation Monte Carlo (ASAMC) algorithm, for neural network training. ASAMC c...
Faming Liang
148
Voted
COLT
2010
Springer
15 years 5 days ago
Forest Density Estimation
We study graph estimation and density estimation in high dimensions, using a family of density estimators based on forest structured undirected graphical models. For density estim...
Anupam Gupta, John D. Lafferty, Han Liu, Larry A. ...
117
Voted
COLT
2010
Springer
15 years 5 days ago
Inferring Descriptive Generalisations of Formal Languages
In the present paper, we introduce a variant of Gold-style learners that is not required to infer precise descriptions of the languages in a class, but that must find descriptive ...
Dominik D. Freydenberger, Daniel Reidenbach
ICML
2010
IEEE
15 years 4 days ago
Comparing Clusterings in Space
This paper proposes a new method for comparing clusterings both partitionally and geometrically. Our approach is motivated by the following observation: the vast majority of previ...
Michael H. Coen, M. Hidayath Ansari, Nathanael Fil...
ICMLA
2009
14 years 12 months ago
Sensitivity Analysis of POMDP Value Functions
In sequential decision making under uncertainty, as in many other modeling endeavors, researchers observe a dynamical system and collect data measuring its behavior over time. The...
Stéphane Ross, Masoumeh T. Izadi, Mark Merc...