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sparse learning

112 papers

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Co-occurring keywords

feature selection (649) convex optimization (1320) l1 regularization (87) stochastic optimization (1060) kernel methods (1096) bayesian inference (1904) group lasso (64) sparse regression (175) gradient descent (1143) sparse optimization (246)

Papers

A* Lasso for Learning a Sparse Bayesian Network Structure for Continuous Variables NIPS 2013
Heterogeneous Visual Features Fusion via Sparse Multimodal Machine CVPR 2013
Sparse Overlapping Sets Lasso for Multitask Learning and its Application to fMRI Analysis NIPS 2013
Multi-task Sparse Learning with Beta Process Prior for Action Recognition CVPR 2013
Structured Sparsity via Alternating Direction Methods JMLR 2012
Online-to-Confidence-Set Conversions and Application to Sparse Stochastic Bandits AISTATS 2012
Learning the Dependency Structure of Latent Factors NIPS 2012
Approximate Message Passing with Consistent Parameter Estimation and Applications to Sparse Learning NIPS 2012
Accelerated Training for Matrix-norm Regularization: A Boosting Approach NIPS 2012
EP-GIG Priors and Applications in Bayesian Sparse Learning JMLR 2012
An Improved GLMNET for L1-regularized Logistic Regression JMLR 2012
Efficient Methods for Overlapping Group Lasso NIPS 2011
Stochastic Methods for -regularized Loss Minimization JMLR 2011
EigenNet: A Bayesian hybrid of generative and conditional models for sparse learning NIPS 2011
Sparse Semi-supervised Learning Using Conjugate Functions JMLR 2010
Multivariate Dyadic Regression Trees for Sparse Learning Problems NIPS 2010
Learning Exponential Families in High-Dimensions: Strong Convexity and Sparsity AISTATS 2010
A Dirty Model for Multi-task Learning NIPS 2010
Learning sparse dynamic linear systems using stable spline kernels and exponential hyperpriors NIPS 2010
Fast Active-set-type Algorithms for $l1$-regularized Linear Regression AISTATS 2010
On the Algorithmics and Applications of a Mixed-norm based Kernel Learning Formulation NIPS 2009
Nonparametric Greedy Algorithms for the Sparse Learning Problem NIPS 2009
Multi-Label Prediction via Sparse Infinite CCA NIPS 2009
A unified framework for high-dimensional analysis of $M$-estimators with decomposable regularizers NIPS 2009
Dual Averaging Method for Regularized Stochastic Learning and Online Optimization NIPS 2009