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ICML
2006
IEEE
16 years 5 months ago
Nightmare at test time: robust learning by feature deletion
When constructing a classifier from labeled data, it is important not to assign too much weight to any single input feature, in order to increase the robustness of the classifier....
Amir Globerson, Sam T. Roweis
ICASSP
2007
IEEE
15 years 11 months ago
Wavelet Footprints and Sparse Bayesian Learning for DNA Copy Number Change Analysis
Alterations in the number of DNA copies are very common in tumor cells and may have a very important role in cancer development and progression. New array platforms provide means ...
Roger Pique-Regi, En-Shuo Tsau, Antonio Ortega, Ro...
156
Voted
ML
2010
ACM
159views Machine Learning» more  ML 2010»
15 years 3 months ago
Algorithms for optimal dyadic decision trees
Abstract A dynamic programming algorithm for constructing optimal dyadic decision trees was recently introduced, analyzed, and shown to be very effective for low dimensional data ...
Don R. Hush, Reid B. Porter
ICML
2010
IEEE
15 years 6 months ago
Proximal Methods for Sparse Hierarchical Dictionary Learning
We propose to combine two approaches for modeling data admitting sparse representations: on the one hand, dictionary learning has proven effective for various signal processing ta...
Rodolphe Jenatton, Julien Mairal, Guillaume Obozin...
ICCV
2003
IEEE
16 years 7 months ago
Learning Pedestrian Models for Silhouette Refinement
We present a model-based method for accurate extraction of pedestrian silhouettes from video sequences. Our approach is based on two assumptions, 1) there is a common appearance t...
L. Lee, Gerald Dalley, Kinh Tieu