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» Sampling Methods for Unsupervised Learning
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77
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JMLR
2010
118views more  JMLR 2010»
14 years 5 months ago
On Over-fitting in Model Selection and Subsequent Selection Bias in Performance Evaluation
Model selection strategies for machine learning algorithms typically involve the numerical optimisation of an appropriate model selection criterion, often based on an estimator of...
Gavin C. Cawley, Nicola L. C. Talbot
116
Voted
SIAMIS
2011
14 years 5 months ago
Large Scale Bayesian Inference and Experimental Design for Sparse Linear Models
Abstract. Many problems of low-level computer vision and image processing, such as denoising, deconvolution, tomographic reconstruction or superresolution, can be addressed by maxi...
Matthias W. Seeger, Hannes Nickisch
ICCV
2009
IEEE
1363views Computer Vision» more  ICCV 2009»
16 years 3 months ago
Human Detection Using Partial Least Squares Analysis
Significant research has been devoted to detecting people in images and videos. In this paper we describe a human detection method that augments widely used edge-based features ...
William Robson Schwartz, Aniruddha Kembhavi, David...
KDD
2010
ACM
304views Data Mining» more  KDD 2010»
14 years 9 months ago
Automatic malware categorization using cluster ensemble
Malware categorization is an important problem in malware analysis and has attracted a lot of attention of computer security researchers and anti-malware industry recently. Todayâ...
Yanfang Ye, Tao Li, Yong Chen, Qingshan Jiang
ICASSP
2011
IEEE
14 years 2 months ago
Collaborative sources identification in mixed signals via hierarchical sparse modeling
A collaborative framework for detecting the different sources in mixed signals is presented in this paper. The approach is based on CHiLasso, a convex collaborative hierarchical s...
Pablo Sprechmann, Ignacio Ramírez, Pablo Ca...