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IVC
2010
128views more  IVC 2010»
13 years 6 months ago
Online kernel density estimation for interactive learning
In this paper we propose a Gaussian-kernel-based online kernel density estimation which can be used for applications of online probability density estimation and online learning. ...
Matej Kristan, Danijel Skocaj, Ales Leonardis
CEC
2008
IEEE
14 years 2 months ago
NichingEDA: Utilizing the diversity inside a population of EDAs for continuous optimization
— Since the Estimation of Distribution Algorithms (EDAs) have been introduced, several single model based EDAs and mixture model based EDAs have been developed. Take Gaussian mod...
Weishan Dong, Xin Yao
NIPS
2004
13 years 9 months ago
Parametric Embedding for Class Visualization
In this paper, we propose a new method, Parametric Embedding (PE), for visualizing the posteriors estimated over a mixture model. PE simultaneously embeds both objects and their c...
Tomoharu Iwata, Kazumi Saito, Naonori Ueda, Sean S...
WSC
2004
13 years 9 months ago
A Large Deviations Perspective on Ordinal Optimization
We consider the problem of optimal allocation of computing budget to maximize the probability of correct selection in the ordinal optimization setting. This problem has been studi...
Peter W. Glynn, Sandeep Juneja
ISCAS
2007
IEEE
136views Hardware» more  ISCAS 2007»
14 years 1 months ago
Flexible Low Power Probability Density Estimation Unit For Speech Recognition
— This paper describes the hardware architecture for a flexible probability density estimation unit to be used in a Large Vocabulary Speech Recognition System, and targeted for m...
Ullas Pazhayaveetil, Dhruba Chandra, Paul Franzon