Communications of the ACM
Bayesian regularization and pruning using a Laplace prior
Neural Computation
The nature of statistical learning theory
The nature of statistical learning theory
Bayesian Classification With Gaussian Processes
IEEE Transactions on Pattern Analysis and Machine Intelligence
Atomic Decomposition by Basis Pursuit
SIAM Journal on Scientific Computing
Machine Learning - The Eleventh Annual Conference on computational Learning Theory
An introduction to support Vector Machines: and other kernel-based learning methods
An introduction to support Vector Machines: and other kernel-based learning methods
AI Game Programming Wisdom
Bayesian Learning for Neural Networks
Bayesian Learning for Neural Networks
Text Categorization Based on Regularized Linear Classification Methods
Information Retrieval
Sparse on-line Gaussian processes
Neural Computation
Joint classifier and feature optimization for cancer diagnosis using gene expression data
RECOMB '03 Proceedings of the seventh annual international conference on Research in computational molecular biology
Generalisation Error Bounds for Sparse Linear Classifiers
COLT '00 Proceedings of the Thirteenth Annual Conference on Computational Learning Theory
Adaptive Sparseness for Supervised Learning
IEEE Transactions on Pattern Analysis and Machine Intelligence
Sparse bayesian learning and the relevance vector machine
The Journal of Machine Learning Research
Pac-bayesian generalisation error bounds for gaussian process classification
The Journal of Machine Learning Research
Rademacher and gaussian complexities: risk bounds and structural results
The Journal of Machine Learning Research
Use of the zero norm with linear models and kernel methods
The Journal of Machine Learning Research
Generalization error bounds for Bayesian mixture algorithms
The Journal of Machine Learning Research
Predictive automatic relevance determination by expectation propagation
ICML '04 Proceedings of the twenty-first international conference on Machine learning
Feature selection, L1 vs. L2 regularization, and rotational invariance
ICML '04 Proceedings of the twenty-first international conference on Machine learning
A Bayesian Approach to Joint Feature Selection and Classifier Design
IEEE Transactions on Pattern Analysis and Machine Intelligence
Learning Overcomplete Representations
Neural Computation
Computational Statistics & Data Analysis
Learning iteratively a classifier with the Bayesian Model Averaging Principle
Pattern Recognition
Automatic covariate selection in logistic models for chest pain diagnosis: A new approach
Computer Methods and Programs in Biomedicine
Classification of proteomic data with multiclass Logistic Partial Least Squares algorithm
International Journal of Bioinformatics Research and Applications
Similarity based smoothing in language modeling
Acta Cybernetica
Algorithms for Sparse Linear Classifiers in the Massive Data Setting
The Journal of Machine Learning Research
Object Class Recognition and Localization Using Sparse Features with Limited Receptive Fields
International Journal of Computer Vision
Bayesian Hyperspectral Image Segmentation with Discriminative Class Learning
IbPRIA '07 Proceedings of the 3rd Iberian conference on Pattern Recognition and Image Analysis, Part I
Parsimonious Kernel Fisher Discrimination
IbPRIA '07 Proceedings of the 3rd Iberian conference on Pattern Recognition and Image Analysis, Part I
ECML PKDD '08 Proceedings of the 2008 European Conference on Machine Learning and Knowledge Discovery in Databases - Part I
Tracking and recognizing actions of multiple hockey players using the boosted particle filter
Image and Vision Computing
Prediction of Transcription Factor Families Using DNA Sequence Features
PRIB '08 Proceedings of the Third IAPR International Conference on Pattern Recognition in Bioinformatics
Fault diagnosis of low speed bearing based on relevance vector machine and support vector machine
Expert Systems with Applications: An International Journal
Sparse multinomial kernel discriminant analysis (sMKDA)
Pattern Recognition
Handwritten word-spotting using hidden Markov models and universal vocabularies
Pattern Recognition
Large-scale sparse logistic regression
Proceedings of the 15th ACM SIGKDD international conference on Knowledge discovery and data mining
Logistic online learning methods and their application to incremental dependency parsing
ACL '07 Proceedings of the 45th Annual Meeting of the ACL: Student Research Workshop
Restart Strategy Selection Using Machine Learning Techniques
SAT '09 Proceedings of the 12th International Conference on Theory and Applications of Satisfiability Testing
A method for large-scale l1-regularized logistic regression
AAAI'07 Proceedings of the 22nd national conference on Artificial intelligence - Volume 1
SATzilla: portfolio-based algorithm selection for SAT
Journal of Artificial Intelligence Research
Learning classifiers when the training data is not IID
IJCAI'07 Proceedings of the 20th international joint conference on Artifical intelligence
Sequence prediction exploiting similarity information
IJCAI'07 Proceedings of the 20th international joint conference on Artifical intelligence
Logistic regression models for a fast CBIR method based on feature selection
IJCAI'07 Proceedings of the 20th international joint conference on Artifical intelligence
Gene identification and survival prediction with Lp Cox regression and novel similarity measure
International Journal of Data Mining and Bioinformatics
A regression model with a hidden logistic process for feature extraction from time series
IJCNN'09 Proceedings of the 2009 international joint conference on Neural Networks
A novel Bayesian logistic discriminant model: An application to face recognition
Pattern Recognition
Point process models for spotting keywords in continuous speech
IEEE Transactions on Audio, Speech, and Language Processing
A Fast Hybrid Algorithm for Large-Scale l1-Regularized Logistic Regression
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
Hierarchical hardness models for SAT
CP'07 Proceedings of the 13th international conference on Principles and practice of constraint programming
SATzilla-07: the design and analysis of an algorithm portfolio for SAT
CP'07 Proceedings of the 13th international conference on Principles and practice of constraint programming
Efficient learning and feature selection in high-dimensional regression
Neural Computation
A bag of notes approach to writer identification in old handwritten musical scores
DAS '10 Proceedings of the 9th IAPR International Workshop on Document Analysis Systems
Identifying emotions, intentions, and attitudes in text using a game with a purpose
CAAGET '10 Proceedings of the NAACL HLT 2010 Workshop on Computational Approaches to Analysis and Generation of Emotion in Text
Learning conditional random fields for classification of hyperspectral images
IEEE Transactions on Image Processing
The Journal of Machine Learning Research
Bayesian kernel projections for classification of high dimensional data
Statistics and Computing
Improving accuracy of microarray classification by a simple multi-task feature selection filter
International Journal of Data Mining and Bioinformatics
Machine learning approaches for high-resolution urban land cover classification: a comparative study
Proceedings of the 2nd International Conference on Computing for Geospatial Research & Applications
An Efficient Approach to Semantic Segmentation
International Journal of Computer Vision
Images as sets of locally weighted features
Computer Vision and Image Understanding
Maximum entropy distribution estimation with generalized regularization
COLT'06 Proceedings of the 19th annual conference on Learning Theory
Fast sparse multinomial regression applied to hyperspectral data
ICIAR'06 Proceedings of the Third international conference on Image Analysis and Recognition - Volume Part II
Face Recognition from Caption-Based Supervision
International Journal of Computer Vision
A supervised clustering approach for fMRI-based inference of brain states
Pattern Recognition
Short communication: On estimating simple probabilistic discriminative models with subclasses
Expert Systems with Applications: An International Journal
Bayesian image segmentation using gaussian field priors
EMMCVPR'05 Proceedings of the 5th international conference on Energy Minimization Methods in Computer Vision and Pattern Recognition
Optimization with Sparsity-Inducing Penalties
Foundations and Trends® in Machine Learning
Editors Choice Article: I2VM: Incremental import vector machines
Image and Vision Computing
Efficient feature selection filters for high-dimensional data
Pattern Recognition Letters
Proceedings of the ACM Conference on Bioinformatics, Computational Biology and Biomedicine
Accurate Prediction of Coronary Artery Disease Using Reliable Diagnosis System
Journal of Medical Systems
Unsupervised classification of SAR images using hierarchical agglomeration and EM
MUSCLE'11 Proceedings of the 2011 international conference on Computational Intelligence for Multimedia Understanding
Joint sparsity-based robust multimodal biometrics recognition
ECCV'12 Proceedings of the 12th international conference on Computer Vision - Volume Part III
Dynamic learning of SCRF for feature selection and classification of hyperspectral imagery
SSPR'12/SPR'12 Proceedings of the 2012 Joint IAPR international conference on Structural, Syntactic, and Statistical Pattern Recognition
Proceedings of the 19th ACM SIGKDD international conference on Knowledge discovery and data mining
IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB)
Discriminative fusion of shape and appearance features for human pose estimation
Pattern Recognition
Multinomial logit models with implicit variable selection
Advances in Data Analysis and Classification
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Recently developed methods for learning sparse classifiers are among the state-of-the-art in supervised learning. These methods learn classifiers that incorporate weighted sums of basis functions with sparsity-promoting priors encouraging the weight estimates to be either significantly large or exactly zero. From a learning-theoretic perspective, these methods control the capacity of the learned classifier by minimizing the number of basis functions used, resulting in better generalization. This paper presents three contributions related to learning sparse classifiers. First, we introduce a true multiclass formulation based on multinomial logistic regression. Second, by combining a bound optimization approach with a component-wise update procedure, we derive fast exact algorithms for learning sparse multiclass classifiers that scale favorably in both the number of training samples and the feature dimensionality, making them applicable even to large data sets in high-dimensional feature spaces. To the best of our knowledge, these are the first algorithms to perform exact multinomial logistic regression with a sparsity-promoting prior. Third, we show how nontrivial generalization bounds can be derived for our classifier in the binary case. Experimental results on standard benchmarkdata sets attest to the accuracy, sparsity, and efficiency of the proposed methods.