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CORR
2012
Springer
183views Education» more  CORR 2012»
12 years 5 months ago
Learning Determinantal Point Processes
Determinantal point processes (DPPs), which arise in random matrix theory and quantum physics, are natural models for subset selection problems where diversity is preferred. Among...
Alex Kulesza, Ben Taskar
ICASSP
2011
IEEE
13 years 1 months ago
Efficient convex optimization for real-time robust beamforming with microphone arrays
This paper presents an efficient implementation of a robust adaptive beamforming algorithm based on convex optimization for applications in the processing-constrained environment...
Eric A. Durant, Ivo Merks, Bill Woods, Jinjun Xiao...
ICDM
2006
IEEE
130views Data Mining» more  ICDM 2006»
14 years 4 months ago
Boosting for Learning Multiple Classes with Imbalanced Class Distribution
Classification of data with imbalanced class distribution has posed a significant drawback of the performance attainable by most standard classifier learning algorithms, which ...
Yanmin Sun, Mohamed S. Kamel, Yang Wang 0007
ICA
2004
Springer
14 years 3 months ago
Blind Signal Separation of Convolutive Mixtures: A Time-Domain Joint-Diagonalization Approach
We address the blind source separation (BSS) problem for the convolutive mixing case. Second-order statistical methods are employed assuming the source signals are non-stationary a...
Marcel Joho
GECCO
2009
Springer
137views Optimization» more  GECCO 2009»
14 years 2 months ago
Efficient natural evolution strategies
Efficient Natural Evolution Strategies (eNES) is a novel alternative to conventional evolutionary algorithms, using the natural gradient to adapt the mutation distribution. Unlike...
Yi Sun, Daan Wierstra, Tom Schaul, Jürgen Sch...