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» Machine Learning with Data Dependent Hypothesis Classes
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ICML
2007
IEEE
14 years 9 months ago
Efficient inference with cardinality-based clique potentials
Many collective labeling tasks require inference on graphical models where the clique potentials depend only on the number of nodes that get a particular label. We design efficien...
Rahul Gupta, Ajit A. Diwan, Sunita Sarawagi
ALT
2006
Springer
14 years 5 months ago
e-Science and the Semantic Web: A Symbiotic Relationship
e-Science is scientific investigation performed through distributed global collaborations between scientists and their resources, and the computing infrastructure that enables this...
Carole A. Goble, Óscar Corcho, Pinar Alper,...
ICML
2010
IEEE
13 years 9 months ago
Gaussian Process Optimization in the Bandit Setting: No Regret and Experimental Design
Many applications require optimizing an unknown, noisy function that is expensive to evaluate. We formalize this task as a multiarmed bandit problem, where the payoff function is ...
Niranjan Srinivas, Andreas Krause, Sham Kakade, Ma...
ICML
2003
IEEE
14 years 9 months ago
Adaptive Overrelaxed Bound Optimization Methods
We study a class of overrelaxed bound optimization algorithms, and their relationship to standard bound optimizers, such as ExpectationMaximization, Iterative Scaling, CCCP and No...
Ruslan Salakhutdinov, Sam T. Roweis
ICML
2003
IEEE
14 years 1 months ago
An Evaluation on Feature Selection for Text Clustering
Feature selection methods have been successfully applied to text categorization but seldom applied to text clustering due to the unavailability of class label information. In this...
Tao Liu, Shengping Liu, Zheng Chen, Wei-Ying Ma