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» A regularization framework for multiple-instance learning
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ICDE
2008
IEEE
203views Database» more  ICDE 2008»
14 years 9 months ago
Training Linear Discriminant Analysis in Linear Time
Linear Discriminant Analysis (LDA) has been a popular method for extracting features which preserve class separability. It has been widely used in many fields of information proces...
Deng Cai, Xiaofei He, Jiawei Han
ICASSP
2008
IEEE
14 years 2 months ago
Sigma-delta resolution enhancement for far-field acoustic source separation
Many source separation algorithms fail to deliver robust performance when applied to signals recorded using highdensity microphone arrays where distance between sensor elements is...
Amin Fazel, Shantanu Chakrabartty
PAMI
2010
337views more  PAMI 2010»
13 years 6 months ago
Single-Image Super-Resolution Using Sparse Regression and Natural Image Prior
—This paper proposes a framework for single-image super-resolution. The underlying idea is to learn a map from input low-resolution images to target high-resolution images based ...
Kwang In Kim, Younghee Kwon
MM
2009
ACM
277views Multimedia» more  MM 2009»
14 years 2 months ago
Inferring semantic concepts from community-contributed images and noisy tags
In this paper, we exploit the problem of inferring images’ semantic concepts from community-contributed images and their associated noisy tags. To infer the concepts more accura...
Jinhui Tang, Shuicheng Yan, Richang Hong, Guo-Jun ...
ML
2010
ACM
127views Machine Learning» more  ML 2010»
13 years 6 months ago
Stability and model selection in k-means clustering
Abstract Clustering Stability methods are a family of widely used model selection techniques for data clustering. Their unifying theme is that an appropriate model should result in...
Ohad Shamir, Naftali Tishby