Atomic Decomposition by Basis Pursuit
SIAM Journal on Scientific Computing
On Model Selection Consistency of Lasso
The Journal of Machine Learning Research
The Group-Lasso for generalized linear models: uniqueness of solutions and efficient algorithms
Proceedings of the 25th international conference on Machine learning
Consistency of the Group Lasso and Multiple Kernel Learning
The Journal of Machine Learning Research
Joint covariate selection and joint subspace selection for multiple classification problems
Statistics and Computing
Online Learning for Matrix Factorization and Sparse Coding
The Journal of Machine Learning Research
Boosting with structure information in the functional space: an application to graph classification
Proceedings of the 16th ACM SIGKDD international conference on Knowledge discovery and data mining
Regularization and feature selection for networked features
CIKM '10 Proceedings of the 19th ACM international conference on Information and knowledge management
Network-based sparse Bayesian classification
Pattern Recognition
Minimum Description Length Penalization for Group and Multi-Task Sparse Learning
The Journal of Machine Learning Research
Conditional topical coding: an efficient topic model conditioned on rich features
Proceedings of the 17th ACM SIGKDD international conference on Knowledge discovery and data mining
Proximal Methods for Hierarchical Sparse Coding
The Journal of Machine Learning Research
Generalized sparse regularization with application to fMRI brain decoding
IPMI'11 Proceedings of the 22nd international conference on Information processing in medical imaging
Gaussian logic for predictive classification
ECML PKDD'11 Proceedings of the 2011 European conference on Machine learning and knowledge discovery in databases - Volume Part II
Sliding window and regression based cup detection in digital fundus images for glaucoma diagnosis
MICCAI'11 Proceedings of the 14th international conference on Medical image computing and computer-assisted intervention - Volume Part III
Towards multi-semantic image annotation with graph regularized exclusive group lasso
MM '11 Proceedings of the 19th ACM international conference on Multimedia
Convex and Network Flow Optimization for Structured Sparsity
The Journal of Machine Learning Research
Structured Variable Selection with Sparsity-Inducing Norms
The Journal of Machine Learning Research
Learning with Structured Sparsity
The Journal of Machine Learning Research
Structured sparse linear graph embedding
Neural Networks
Extracting non-negative basis images using pixel dispersion penalty
Pattern Recognition
Optimization with Sparsity-Inducing Penalties
Foundations and Trends® in Machine Learning
Structured sparsity and generalization
The Journal of Machine Learning Research
Feature grouping and selection over an undirected graph
Proceedings of the 18th ACM SIGKDD international conference on Knowledge discovery and data mining
Structured sparsity via alternating direction methods
The Journal of Machine Learning Research
Label-to-region with continuity-biased bi-layer sparsity priors
ACM Transactions on Multimedia Computing, Communications, and Applications (TOMCCAP)
Annotating web images using NOVA: NOn-conVex group spArsity
Proceedings of the 20th ACM international conference on Multimedia
Fast approximations to structured sparse coding and applications to object classification
ECCV'12 Proceedings of the 12th European conference on Computer Vision - Volume Part V
Sparse methods for biomedical data
ACM SIGKDD Explorations Newsletter
Group sparse topical coding: from code to topic
Proceedings of the sixth ACM international conference on Web search and data mining
Regularizers for structured sparsity
Advances in Computational Mathematics
FeaFiner: biomarker identification from medical data through feature generalization and selection
Proceedings of the 19th ACM SIGKDD international conference on Knowledge discovery and data mining
Supervised feature selection in graphs with path coding penalties and network flows
The Journal of Machine Learning Research
Group subset selection for linear regression
Computational Statistics & Data Analysis
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We propose a new penalty function which, when used as regularization for empirical risk minimization procedures, leads to sparse estimators. The support of the sparse vector is typically a union of potentially overlapping groups of co-variates defined a priori, or a set of covariates which tend to be connected to each other when a graph of covariates is given. We study theoretical properties of the estimator, and illustrate its behavior on simulated and breast cancer gene expression data.