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» From Margin to Sparsity
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ICIP
2010
IEEE
14 years 12 months ago
Single image deblurring with adaptive dictionary learning
We propose a motion deblurring algorithm that exploits sparsity constraints of image patches using one single frame. In our formulation, each image patch is encoded with sparse co...
Zhe Hu, Jia-Bin Huang, Ming-Hsuan Yang
PAMI
2011
14 years 4 months ago
Hidden Part Models for Human Action Recognition: Probabilistic versus Max Margin
—We present a discriminative part-based approach for human action recognition from video sequences using motion features. Our model is based on the recently proposed hidden condi...
Yang Wang 0003, Greg Mori
FLAIRS
2000
15 years 3 months ago
Overriding the Experts: A Stacking Method for Combining Marginal Classifiers
The design of an optimal Bayesian classifier for multiple features is dependent on the estimation of multidimensional joint probability density functions and therefore requires a ...
Mark D. Happel, Peter Bock
121
Voted
ICDM
2009
IEEE
175views Data Mining» more  ICDM 2009»
14 years 11 months ago
Maximum Margin Clustering with Multivariate Loss Function
This paper presents a simple but powerful extension of the maximum margin clustering (MMC) algorithm that optimizes multivariate performance measure specifically defined for clust...
Bin Zhao, James Tin-Yau Kwok, Changshui Zhang
99
Voted
NIPS
2007
15 years 3 months ago
The Generalized FITC Approximation
We present an efficient generalization of the sparse pseudo-input Gaussian process (SPGP) model developed by Snelson and Ghahramani [1], applying it to binary classification pro...
Andrew Naish-Guzman, Sean B. Holden