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» A regularization framework for multiple-instance learning
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ICASSP
2008
IEEE
14 years 2 months ago
Modulation analysis of speech through orthogonal FIR filterbank optimization
Newborns must learn to structure incoming acoustic information into segments, words, phrases, etc., before they can start to learn language. This process is thought to rely on mod...
Jonathan Le Roux, Hirokazu Kameoka, Nobutaka Ono, ...
DAGM
2007
Springer
14 years 1 months ago
Image Statistics and Local Spatial Conditions for Nonstationary Blurred Image Reconstruction
Deblurring is important in many visual systems. This paper presents a novel approach for nonstationary blurred image reconstruction with ringing reduction in a variational Bayesian...
Hongwei Zheng, Olaf Hellwich
PAMI
2012
11 years 10 months ago
A Least-Squares Framework for Component Analysis
— Over the last century, Component Analysis (CA) methods such as Principal Component Analysis (PCA), Linear Discriminant Analysis (LDA), Canonical Correlation Analysis (CCA), Lap...
Fernando De la Torre
JMLR
2008
169views more  JMLR 2008»
13 years 7 months ago
Multi-class Discriminant Kernel Learning via Convex Programming
Regularized kernel discriminant analysis (RKDA) performs linear discriminant analysis in the feature space via the kernel trick. Its performance depends on the selection of kernel...
Jieping Ye, Shuiwang Ji, Jianhui Chen
CVPR
2008
IEEE
14 years 9 months ago
Rank-based distance metric learning: An application to image retrieval
We present a novel approach to learn distance metric for information retrieval. Learning distance metric from a number of queries with side information, i.e., relevance judgements...
Jung-Eun Lee, Rong Jin, Anil K. Jain