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ECCV
2010
Springer
15 years 4 months ago
Efficient Highly Over-Complete Sparse Coding using a Mixture Model
Sparse coding of sensory data has recently attracted notable attention in research of learning useful features from the unlabeled data. Empirical studies show that mapping the data...
GECCO
2007
Springer
180views Optimization» more  GECCO 2007»
15 years 3 months ago
Support vector regression for classifier prediction
In this paper we introduce XCSF with support vector prediction: the problem of learning the prediction function is solved as a support vector regression problem and each classifie...
Daniele Loiacono, Andrea Marelli, Pier Luca Lanzi
WSC
2000
15 years 1 months ago
Variance reduction techniques for value-at-risk with heavy-tailed risk factors
The calculation of value-at-risk (VAR) for large portfolios of complex instruments is among the most demanding and widespread computational challenges facing the financial industr...
Paul Glasserman, Philip Heidelberger, Perwez Shaha...
CORR
2010
Springer
95views Education» more  CORR 2010»
14 years 12 months ago
Statistical Compressive Sensing of Gaussian Mixture Models
A new framework of compressive sensing (CS), namely statistical compressive sensing (SCS), that aims at efficiently sampling a collection of signals that follow a statistical dist...
Guoshen Yu, Guillermo Sapiro
CORR
2008
Springer
179views Education» more  CORR 2008»
14 years 12 months ago
Distributed Parameter Estimation in Sensor Networks: Nonlinear Observation Models and Imperfect Communication
The paper studies the problem of distributed static parameter (vector) estimation in sensor networks with nonlinear observation models and imperfect inter-sensor communication. We...
Soummya Kar, José M. F. Moura, Kavita Raman...