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NIPS
2004
15 years 1 months ago
Semi-supervised Learning by Entropy Minimization
We consider the semi-supervised learning problem, where a decision rule is to be learned from labeled and unlabeled data. In this framework, we motivate minimum entropy regulariza...
Yves Grandvalet, Yoshua Bengio
CORR
2006
Springer
99views Education» more  CORR 2006»
14 years 11 months ago
PAC Learning Mixtures of Axis-Aligned Gaussians with No Separation Assumption
Abstract. We propose and analyze a new vantage point for the learning of mixtures of Gaussians: namely, the PAC-style model of learning probability distributions introduced by Kear...
Jon Feldman, Ryan O'Donnell, Rocco A. Servedio
EVOW
2007
Springer
15 years 6 months ago
Robust Peak Detection and Alignment of nanoLC-FT Mass Spectrometry Data
In liquid chromatography-mass spectrometry (LC-MS) based expression proteomics, samples from different groups are analyzed comparatively in order to detect differences that can p...
Marius C. Codrea, Connie R. Jimenez, Sander R. Pie...
ICMCS
2008
IEEE
115views Multimedia» more  ICMCS 2008»
15 years 6 months ago
Spatial pyramid mining for logo detection in natural scenes
This work introduces a novel data mining scheme, spatial pyramid mining, to discover association rules at multiple resolutions in order to identify frequent spatial configuration...
Jim Kleban, Xing Xie, Wei-Ying Ma
CVPR
2008
IEEE
16 years 1 months ago
Sequential sparsification for change detection
This paper presents a general method for segmenting a vector valued sequence into an unknown number of subsequences where all data points from a subsequence can be represented wit...
Necmiye Ozay, Mario Sznaier, Octavia I. Camps