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ICML
2007
IEEE
15 years 10 months ago
Sparse probabilistic classifiers
The scores returned by support vector machines are often used as a confidence measures in the classification of new examples. However, there is no theoretical argument sustaining ...
Romain Hérault, Yves Grandvalet
ICDM
2009
IEEE
172views Data Mining» more  ICDM 2009»
15 years 4 months ago
Sparse Least-Squares Methods in the Parallel Machine Learning (PML) Framework
—We describe parallel methods for solving large-scale, high-dimensional, sparse least-squares problems that arise in machine learning applications such as document classificatio...
Ramesh Natarajan, Vikas Sindhwani, Shirish Tatikon...
WSOM
2009
Springer
15 years 4 months ago
Sparse Linear Combination of SOMs for Data Imputation: Application to Financial Database
Abstract. This paper presents a new methodology for missing value imputation in a database. The methodology combines the outputs of several Self-Organizing Maps in order to obtain ...
Antti Sorjamaa, Francesco Corona, Yoan Miche, Paul...
ICASSP
2008
IEEE
15 years 4 months ago
Frequency domain selective tap adaptive algorithms for sparse system identification
We propose a new low complexity and fast converging frequencydomain adaptive algorithm for sparse system identification. This is achieved by exploiting the MMax and SP tap-select...
Andy W. H. Khong, Xiang Lin, Milos Doroslovacki, P...
ICMCS
2008
IEEE
151views Multimedia» more  ICMCS 2008»
15 years 4 months ago
Fast keyword detection with sparse time-frequency models
We address the problem of keyword spotting in continuous speech streams when training and testing conditions can be different. We propose a keyword spotting algorithm based on spa...
Effrosini Kokiopoulou, Pascal Frossard, Olivier Ve...