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» On Learning with Integral Operators
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CVPR
2011
IEEE
15 years 2 months ago
Distributed Computer Vision Algorithms Through Distributed Averaging
Traditional computer vision and machine learning algorithms have been largely studied in a centralized setting, where all the processing is performed at a single central location....
Roberto Tron, René, Vidal
IJNSEC
2010
128views more  IJNSEC 2010»
15 years 1 months ago
New Efficient Searchable Encryption Schemes from Bilinear Pairings
Public key encryption with keyword search (PEKS) enables user Alice to send a secret key TW to a server that will enable the server to locate all encrypted messages containing the...
Chunxiang Gu, Yuefei Zhu
TSP
2010
15 years 1 months ago
Testing stationarity with surrogates: a time-frequency approach
An operational framework is developed for testing stationarity relatively to an observation scale, in both stochastic and deterministic contexts. The proposed method is based on a ...
Pierre Borgnat, Patrick Flandrin, Paul Honeine, C&...
ICASSP
2011
IEEE
14 years 10 months ago
A partial least squares framework for speaker recognition
Modern approaches to speaker recognition (verification) operate in a space of “supervectors” created via concatenation of the mean vectors of a Gaussian mixture model (GMM) a...
Balaji Vasan Srinivasan, Dmitry N. Zotkin, Ramani ...
ICASSP
2011
IEEE
14 years 10 months ago
Proportionate-type normalized least mean square algorithm with gain allocation motivated by minimization of mean-square-weight d
In previous work, a water-filling algorithm was proposed which sought to minimize the mean square error (MSE) at any given time by optimally choosing the gains (i.e. step-sizes) ...
Kevin T. Wagner, Milos Doroslovacki