Communications of the ACM
The Strength of Weak Learnability
Machine Learning
A training algorithm for optimal margin classifiers
COLT '92 Proceedings of the fifth annual workshop on Computational learning theory
The design and analysis of efficient learning algorithms
The design and analysis of efficient learning algorithms
On the convergence of the coordinate descent method for convex differentiable minimization
Journal of Optimization Theory and Applications
Stable exponential-penalty algorithm with superlinear convergence
Journal of Optimization Theory and Applications
The nature of statistical learning theory
The nature of statistical learning theory
Game theory, on-line prediction and boosting
COLT '96 Proceedings of the ninth annual conference on Computational learning theory
Inducing Features of Random Fields
IEEE Transactions on Pattern Analysis and Machine Intelligence
Improved boosting algorithms using confidence-rated predictions
COLT' 98 Proceedings of the eleventh annual conference on Computational learning theory
Boosting in the limit: maximizing the margin of learned ensembles
AAAI '98/IAAI '98 Proceedings of the fifteenth national/tenth conference on Artificial intelligence/Innovative applications of artificial intelligence
Nonlinear component analysis as a kernel eigenvalue problem
Neural Computation
Parsimonious Least Norm Approximation
Computational Optimization and Applications
Atomic Decomposition by Basis Pursuit
SIAM Journal on Scientific Computing
Boosting as entropy projection
COLT '99 Proceedings of the twelfth annual conference on Computational learning theory
Prediction games and arcing algorithms
Neural Computation
An introduction to support Vector Machines: and other kernel-based learning methods
An introduction to support Vector Machines: and other kernel-based learning methods
Machine Learning
Neural Networks for Pattern Recognition
Neural Networks for Pattern Recognition
Neural Networks: A Comprehensive Foundation
Neural Networks: A Comprehensive Foundation
Parallel Optimization: Theory, Algorithms and Applications
Parallel Optimization: Theory, Algorithms and Applications
An Interior Proximal Algorithm and the Exponential Multiplier Method for Semidefinite Programming
SIAM Journal on Optimization
Mathematical Programming in Data Mining
Data Mining and Knowledge Discovery
A Tutorial on Support Vector Machines for Pattern Recognition
Data Mining and Knowledge Discovery
Linear Programming Boosting via Column Generation
Machine Learning
Sparse Regression Ensembles in Infinite and Finite Hypothesis Spaces
Machine Learning
New Methods for Splice Site Recognition
ICANN '02 Proceedings of the International Conference on Artificial Neural Networks
AdaBoosting Neural Networks: Application to on-line Character Recognition
ICANN '97 Proceedings of the 7th International Conference on Artificial Neural Networks
A decision-theoretic generalization of on-line learning and an application to boosting
EuroCOLT '95 Proceedings of the Second European Conference on Computational Learning Theory
COLT '00 Proceedings of the Thirteenth Annual Conference on Computational Learning Theory
COLT '00 Proceedings of the Thirteenth Annual Conference on Computational Learning Theory
Logistic Regression, AdaBoost and Bregman Distances
COLT '00 Proceedings of the Thirteenth Annual Conference on Computational Learning Theory
Extensions of a Theory of Networks for Approximation and Learning: Dimensionality Reduction and Clustering
Estimating the Support of a High-Dimensional Distribution
Neural Computation
An empirical evaluation of bagging and boosting
AAAI'97/IAAI'97 Proceedings of the fourteenth national conference on artificial intelligence and ninth conference on Innovative applications of artificial intelligence
An introduction to kernel-based learning algorithms
IEEE Transactions on Neural Networks
IEEE Transactions on Pattern Analysis and Machine Intelligence
An introduction to boosting and leveraging
Advanced lectures on machine learning
Novelty detection: a review—part 2: neural network based approaches
Signal Processing
Estimation of High-Density Regions Using One-Class Neighbor Machines
IEEE Transactions on Pattern Analysis and Machine Intelligence
Different Paradigms for Choosing Sequential Reweighting Algorithms
Neural Computation
IEEE Transactions on Pattern Analysis and Machine Intelligence
An online support vector machine for abnormal events detection
Signal Processing - Special section: Advances in signal processing-assisted cross-layer designs
Neural Computation
Automatic hardware implementation tool for a discrete Adaboost-based decision algorithm
EURASIP Journal on Applied Signal Processing
Support Vector Machinery for Infinite Ensemble Learning
The Journal of Machine Learning Research
ACM Computing Surveys (CSUR)
A new model of multi-class support vector machine with parameter υ
FSKD'09 Proceedings of the 6th international conference on Fuzzy systems and knowledge discovery - Volume 1
LACBoost and FisherBoost: optimally building cascade classifiers
ECCV'10 Proceedings of the 11th European conference on Computer vision: Part II
Journal of Real-Time Image Processing
Language Resources and Evaluation
Asymmetric totally-corrective boosting for real-time object detection
ACCV'10 Proceedings of the 10th Asian conference on Computer vision - Volume Part I
Expert Systems with Applications: An International Journal
A new approach for classification: visual simulation point of view
ISNN'05 Proceedings of the Second international conference on Advances in neural networks - Volume Part II
Large-Margin thresholded ensembles for ordinal regression: theory and practice
ALT'06 Proceedings of the 17th international conference on Algorithmic Learning Theory
A cascaded mixture SVM classifier for object detection
ISNN'05 Proceedings of the Second international conference on Advances in Neural Networks - Volume Part I
A naive solution to the one-class problem and its extension to kernel methods
CIARP'05 Proceedings of the 10th Iberoamerican Congress conference on Progress in Pattern Recognition, Image Analysis and Applications
A boosting SVM chain learning for visual information retrieval
ISNN'06 Proceedings of the Third international conference on Advances in Neural Networks - Volume Part I
Pseudo relevance feedback based on iterative probabilistic one-class SVMs in web image retrieval
PCM'04 Proceedings of the 5th Pacific Rim Conference on Advances in Multimedia Information Processing - Volume Part II
Some marginal learning algorithms for unsupervised problems
ISI'05 Proceedings of the 2005 IEEE international conference on Intelligence and Security Informatics
Training regression ensembles by sequential target correction and resampling
Information Sciences: an International Journal
Event-based classification of social media streams
Proceedings of the 2nd ACM International Conference on Multimedia Retrieval
One-class classification with Gaussian processes
Pattern Recognition
1-norm support vector novelty detection and its sparseness
Neural Networks
Clustering-based ensembles for one-class classification
Information Sciences: an International Journal
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We show via an equivalence of mathematical programs that a support vector (SV) algorithm can be translated into an equivalent boosting-like algorithm and vice versa. We exemplify this translation procedure for a new algorithm驴one-class leveraging驴starting from the one-class support vector machine (1-SVM). This is a first step toward unsupervised learning in a boosting framework. Building on so-called barrier methods known from the theory of constrained optimization, it returns a function, written as a convex combination of base hypotheses, that characterizes whether a given test point is likely to have been generated from the distribution underlying the training data. Simulations on one-class classification problems demonstrate the usefulness of our approach.