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JMLR
2012
12 years 15 days ago
Conditional Likelihood Maximisation: A Unifying Framework for Information Theoretic Feature Selection
We present a unifying framework for information theoretic feature selection, bringing almost two decades of research on heuristic filter criteria under a single theoretical inter...
Gavin Brown, Adam Pocock, Ming-Jie Zhao, Mikel Luj...
JMLR
2012
12 years 15 days ago
Random Search for Hyper-Parameter Optimization
Grid search and manual search are the most widely used strategies for hyper-parameter optimization. This paper shows empirically and theoretically that randomly chosen trials are ...
James Bergstra, Yoshua Bengio
JMLR
2012
12 years 15 days ago
Bounding the Probability of Error for High Precision Optical Character Recognition
We consider a model for which it is important, early in processing, to estimate some variables with high precision, but perhaps at relatively low recall. If some variables can be ...
Gary B. Huang, Andrew Kae, Carl Doersch, Erik G. L...
JMLR
2012
12 years 15 days ago
Minimax-Optimal Rates For Sparse Additive Models Over Kernel Classes Via Convex Programming
Sparse additive models are families of d-variate functions with the additive decomposition f∗ = ∑j∈S f∗ j , where S is an unknown subset of cardinality s d. In this paper,...
Garvesh Raskutti, Martin J. Wainwright, Bin Yu
JMLR
2012
12 years 15 days ago
Metric and Kernel Learning Using a Linear Transformation
Metric and kernel learning arise in several machine learning applications. However, most existing metric learning algorithms are limited to learning metrics over low-dimensional d...
Prateek Jain, Brian Kulis, Jason V. Davis, Inderji...