← Core Methods
Machine Learning › Core Methods ›

Feature Selection

462 directly classified papers

Papers per year

Papers

Moreau-Yosida Regularization for Grouped Tree Structure Learning NIPS 2010
Local Causal and Markov Blanket Induction for Causal Discovery and Feature Selection for Classification Part I: Algorithms and Empirical Evaluation JMLR 2010
Accounting for network effects in neuronal responses using L1 regularized point process models NIPS 2010
Block Variable Selection in Multivariate Regression and High-dimensional Causal Inference NIPS 2010
Sufficient Conditions for Generating Group Level Sparsity in a Robust Minimax Framework NIPS 2010
Structured sparsity-inducing norms through submodular functions NIPS 2010
Efficient and Robust Feature Selection via Joint ℓ2,1-Norms Minimization NIPS 2010
Heterogeneous multitask learning with joint sparsity constraints NIPS 2009
Sparse Estimation Using General Likelihoods and Non-Factorial Priors NIPS 2009
Learning Brain Connectivity of Alzheimer's Disease from Neuroimaging Data NIPS 2009
Nonparametric Greedy Algorithms for the Sparse Learning Problem NIPS 2009
Orthogonal Matching Pursuit From Noisy Random Measurements: A New Analysis NIPS 2009
Grouped Orthogonal Matching Pursuit for Variable Selection and Prediction NIPS 2009
Unsupervised Feature Selection for the $k$-means Clustering Problem NIPS 2009
Submodularity Cuts and Applications NIPS 2009
Exploring Functional Connectivities of the Human Brain using Multivariate Information Analysis NIPS 2009
Sparsistent Learning of Varying-coefficient Models with Structural Changes NIPS 2009
Toward Provably Correct Feature Selection in Arbitrary Domains NIPS 2009
Dynamic visual attention: searching for coding length increments NIPS 2008
Model Selection in Gaussian Graphical Models: High-Dimensional Consistency of \boldmath$\ell_1$-regularized MLE NIPS 2008
High-dimensional support union recovery in multivariate regression NIPS 2008
Nonparametric regression and classification with joint sparsity constraints NIPS 2008
Exploring Large Feature Spaces with Hierarchical Multiple Kernel Learning NIPS 2008
Multi-stage Convex Relaxation for Learning with Sparse Regularization NIPS 2008
Adaptive Forward-Backward Greedy Algorithm for Sparse Learning with Linear Models NIPS 2008