Efficient projections onto the l1-ball for learning in high dimensions
Proceedings of the 25th international conference on Machine learning
Algorithms for Sparse Linear Classifiers in the Massive Data Setting
The Journal of Machine Learning Research
Trust Region Newton Method for Logistic Regression
The Journal of Machine Learning Research
Exponentiated Gradient Algorithms for Conditional Random Fields and Max-Margin Markov Networks
The Journal of Machine Learning Research
Boosting with structural sparsity
ICML '09 Proceedings of the 26th Annual International Conference on Machine Learning
Efficient Euclidean projections in linear time
ICML '09 Proceedings of the 26th Annual International Conference on Machine Learning
Stochastic methods for l1 regularized loss minimization
ICML '09 Proceedings of the 26th Annual International Conference on Machine Learning
Large-scale sparse logistic regression
Proceedings of the 15th ACM SIGKDD international conference on Knowledge discovery and data mining
Data-driven text features for sponsored search click prediction
Proceedings of the Third International Workshop on Data Mining and Audience Intelligence for Advertising
Optimal estimation of deterioration from diagnostic image sequence
IEEE Transactions on Signal Processing
Sparse reconstruction by separable approximation
IEEE Transactions on Signal Processing
Fast communication: Mixed linear system estimation and identification
Signal Processing
Exponential family sparse coding with applications to self-taught learning
IJCAI'09 Proceedings of the 21st international jont conference on Artifical intelligence
Distributed large scale network utility maximization
ISIT'09 Proceedings of the 2009 IEEE international conference on Symposium on Information Theory - Volume 2
Learning locomotion over rough terrain using terrain templates
IROS'09 Proceedings of the 2009 IEEE/RSJ international conference on Intelligent robots and systems
Efficient Online and Batch Learning Using Forward Backward Splitting
The Journal of Machine Learning Research
Fingerprinting the datacenter: automated classification of performance crises
Proceedings of the 5th European conference on Computer systems
A Fast Hybrid Algorithm for Large-Scale l1-Regularized Logistic Regression
The Journal of Machine Learning Research
Iterative Scaling and Coordinate Descent Methods for Maximum Entropy Models
The Journal of Machine Learning Research
Multiplicative updates for L1-regularized linear and logistic regression
IDA'07 Proceedings of the 7th international conference on Intelligent data analysis
Toward automatic policy refinement in repair services for large distributed systems
ACM SIGOPS Operating Systems Review
Combined regression and ranking
Proceedings of the 16th ACM SIGKDD international conference on Knowledge discovery and data mining
Hunting for problems with Artemis
WASL'08 Proceedings of the First USENIX conference on Analysis of system logs
SysML'08 Proceedings of the Third conference on Tackling computer systems problems with machine learning techniques
Novel biological network features discovery for in silico identification of drug targets
Proceedings of the 1st ACM International Health Informatics Symposium
Face liveness detection from a single image with sparse low rank bilinear discriminative model
ECCV'10 Proceedings of the 11th European conference on Computer vision: Part VI
Expert Systems with Applications: An International Journal
Learning, planning, and control for quadruped locomotion over challenging terrain
International Journal of Robotics Research
Computational Statistics & Data Analysis
Recovering Occlusion Boundaries from an Image
International Journal of Computer Vision
Dual Averaging Methods for Regularized Stochastic Learning and Online Optimization
The Journal of Machine Learning Research
The Journal of Machine Learning Research
Multitask Sparsity via Maximum Entropy Discrimination
The Journal of Machine Learning Research
A coordinate gradient descent method for l1-regularized convex minimization
Computational Optimization and Applications
An improved GLMNET for l1-regularized logistic regression
Proceedings of the 17th ACM SIGKDD international conference on Knowledge discovery and data mining
Super-Linear Convergence of Dual Augmented Lagrangian Algorithm for Sparsity Regularized Estimation
The Journal of Machine Learning Research
Stochastic Methods for l1-regularized Loss Minimization
The Journal of Machine Learning Research
Proceedings of the 4th ACM workshop on Security and artificial intelligence
Identifying users from their rating patterns
Proceedings of the 2nd Challenge on Context-Aware Movie Recommendation
Foundations and Trends® in Machine Learning
Optimization with Sparsity-Inducing Penalties
Foundations and Trends® in Machine Learning
Coordinate ascent for penalized semiparametric regression on high-dimensional panel count data
Computational Statistics & Data Analysis
Accelerated Block-coordinate Relaxation for Regularized Optimization
SIAM Journal on Optimization
Reinforcement learning transfer via sparse coding
Proceedings of the 11th International Conference on Autonomous Agents and Multiagent Systems - Volume 1
Manifold identification in dual averaging for regularized stochastic online learning
The Journal of Machine Learning Research
An improved GLMNET for L1-regularized logistic regression
The Journal of Machine Learning Research
Proceedings of the ACM Conference on Bioinformatics, Computational Biology and Biomedicine
MICCAI'12 Proceedings of the 15th international conference on Medical Image Computing and Computer-Assisted Intervention - Volume Part I
Simplified labeling process for medical image segmentation
MICCAI'12 Proceedings of the 15th international conference on Medical Image Computing and Computer-Assisted Intervention - Volume Part II
Stochastic coordinate descent methods for regularized smooth and nonsmooth losses
ECML PKDD'12 Proceedings of the 2012 European conference on Machine Learning and Knowledge Discovery in Databases - Volume Part I
Sparse methods for biomedical data
ACM SIGKDD Explorations Newsletter
Reinforcement learning transfer using a sparse coded inter-task mapping
EUMAS'11 Proceedings of the 9th European conference on Multi-Agent Systems
Towards efficient sparse coding for scalable image annotation
Proceedings of the 21st ACM international conference on Multimedia
The role of dictionary learning on sparse representation-based classification
Proceedings of the 6th International Conference on PErvasive Technologies Related to Assistive Environments
Object class detection: A survey
ACM Computing Surveys (CSUR)
Fast Design Exploration for Performance, Power and Accuracy Tradeoffs in FPGA-Based Accelerators
ACM Transactions on Reconfigurable Technology and Systems (TRETS)
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Logistic regression with l1 regularization has been proposed as a promising method for feature selection in classification problems. In this paper we describe an efficient interior-point method for solving large-scale l1-regularized logistic regression problems. Small problems with up to a thousand or so features and examples can be solved in seconds on a PC; medium sized problems, with tens of thousands of features and examples, can be solved in tens of seconds (assuming some sparsity in the data). A variation on the basic method, that uses a preconditioned conjugate gradient method to compute the search step, can solve very large problems, with a million features and examples (e.g., the 20 Newsgroups data set), in a few minutes, on a PC. Using warm-start techniques, a good approximation of the entire regularization path can be computed much more efficiently than by solving a family of problems independently.