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PRL
2011
14 years 7 months ago
A sparse version of the ridge logistic regression for large-scale text categorization
The ridge logistic regression has successfully been used in text categorization problems and it has been shown to reach the same performance as the Support Vector Machine but with...
Sujeevan Aseervatham, Anestis Antoniadis, É...
119
Voted
TIP
2010
141views more  TIP 2010»
14 years 7 months ago
Efficient Particle Filtering via Sparse Kernel Density Estimation
Particle filters (PFs) are Bayesian filters capable of modeling nonlinear, non-Gaussian, and nonstationary dynamical systems. Recent research in PFs has investigated ways to approp...
Amit Banerjee, Philippe Burlina
AAAI
2012
13 years 3 months ago
Sparse Probabilistic Relational Projection
Probabilistic relational PCA (PRPCA) can learn a projection matrix to perform dimensionality reduction for relational data. However, the results learned by PRPCA lack interpretabi...
Wu-Jun Li, Dit-Yan Yeung
122
Voted
VC
2008
95views more  VC 2008»
15 years 19 days ago
1001 Acquisition viewpoints: efficient and versatile view-dependent modeling of real-world scenes
Modeling is a severe bottleneck for computer graphics applications. Manual modeling is time consuming and fails to capture the complexity of real world scenes. Automated modeling b...
Mihai Mudure, Voicu Popescu
JMLR
2011
148views more  JMLR 2011»
14 years 7 months ago
Bayesian Generalized Kernel Mixed Models
We propose a fully Bayesian methodology for generalized kernel mixed models (GKMMs), which are extensions of generalized linear mixed models in the feature space induced by a repr...
Zhihua Zhang, Guang Dai, Michael I. Jordan