A training algorithm for optimal margin classifiers
COLT '92 Proceedings of the fifth annual workshop on Computational learning theory
Numerical recipes in C (2nd ed.): the art of scientific computing
Numerical recipes in C (2nd ed.): the art of scientific computing
C4.5: programs for machine learning
C4.5: programs for machine learning
The nature of statistical learning theory
The nature of statistical learning theory
Machine Learning
Machine Learning
Game theory, on-line prediction and boosting
COLT '96 Proceedings of the ninth annual conference on Computational learning theory
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
Using support vector machines for time series prediction
Advances in kernel methods
Combining support vector and mathematical programming methods for classification
Advances in kernel methods
Proceedings of the 1998 conference on Advances in neural information processing systems II
Improved Generalization Through Explicit Optimization of Margins
Machine Learning
Neural Networks for Pattern Recognition
Neural Networks for Pattern Recognition
Boosting the margin: A new explanation for the effectiveness of voting methods
ICML '97 Proceedings of the Fourteenth International Conference on Machine Learning
AdaBoosting Neural Networks: Application to on-line Character Recognition
ICANN '97 Proceedings of the 7th International Conference on Artificial Neural Networks
A Boosting Algorithm for Regression
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
ALT '96 Proceedings of the 7th International Workshop on Algorithmic Learning Theory
Neural Computation
Machine Learning
Choosing Multiple Parameters for Support Vector Machines
Machine Learning
Boosting Methods for Regression
Machine Learning
Sparse Regression Ensembles in Infinite and Finite Hypothesis Spaces
Machine Learning
Logistic Regression, AdaBoost and Bregman Distances
Machine Learning
Constructing Boosting Algorithms from SVMs: An Application to One-Class Classification
IEEE Transactions on Pattern Analysis and Machine Intelligence
Natural discriminant analysis using interactive Potts models
Neural Computation
A new discriminative kernel from probabilistic models
Neural Computation
Analysis of the Performance of AdaBoost.M2 for the Simulated Digit-Recognition-Example
EMCL '01 Proceedings of the 12th European Conference on Machine Learning
A Mixed Ensemble Approach for the Semi-supervised Problem
ICANN '02 Proceedings of the International Conference on Artificial Neural Networks
Boosting Mixture Models for Semi-supervised Learning
ICANN '01 Proceedings of the International Conference on Artificial Neural Networks
Robust Ensemble Learning for Data Mining
PADKK '00 Proceedings of the 4th Pacific-Asia Conference on Knowledge Discovery and Data Mining, Current Issues and New Applications
Optimization of the SVM Kernels Using an Empirical Error Minimization Scheme
SVM '02 Proceedings of the First International Workshop on Pattern Recognition with Support Vector Machines
Highlighting Hard Patterns via AdaBoost Weights Evolution
MCS '02 Proceedings of the Third International Workshop on Multiple Classifier Systems
Maximizing the Margin with Boosting
COLT '02 Proceedings of the 15th Annual Conference on Computational Learning Theory
Optimizing a Multiple Classifier System
PRICAI '02 Proceedings of the 7th Pacific Rim International Conference on Artificial Intelligence: Trends in Artificial Intelligence
Minimum majority classification and boosting
Eighteenth national conference on Artificial intelligence
Machine Learning
An introduction to boosting and leveraging
Advanced lectures on machine learning
Ho--Kashyap classifier with generalization control
Pattern Recognition Letters
Bayesian trigonometric support vector classifier
Neural Computation
Reducing multiclass to binary: a unifying approach for margin classifiers
The Journal of Machine Learning Research
Sparse bayesian learning and the relevance vector machine
The Journal of Machine Learning Research
The Journal of Machine Learning Research
Variable selection using svm based criteria
The Journal of Machine Learning Research
Improvement of Boosting Algorithm by Modifying the Weighting Rule
Annals of Mathematics and Artificial Intelligence
Online Choice of Active Learning Algorithms
The Journal of Machine Learning Research
A Compression Approach to Support Vector Model Selection
The Journal of Machine Learning Research
Robust feature induction for support vector machines
ICML '04 Proceedings of the twenty-first international conference on Machine learning
Predictive automatic relevance determination by expectation propagation
ICML '04 Proceedings of the twenty-first international conference on Machine learning
Boosting as a Regularized Path to a Maximum Margin Classifier
The Journal of Machine Learning Research
Training algorithms for fuzzy support vector machines with noisy data
Pattern Recognition Letters
The Dynamics of AdaBoost: Cyclic Behavior and Convergence of Margins
The Journal of Machine Learning Research
Semisupervised Learning for Molecular Profiling
IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB)
A smoothed boosting algorithm using probabilistic output codes
ICML '05 Proceedings of the 22nd international conference on Machine learning
Bit Reduction Support Vector Machine
ICDM '05 Proceedings of the Fifth IEEE International Conference on Data Mining
The Synergy Between PAV and AdaBoost
Machine Learning
Robustifying AdaBoost by Adding the Naive Error Rate
Neural Computation
Different Paradigms for Choosing Sequential Reweighting Algorithms
Neural Computation
Neural Networks - 2005 Special issue: IJCNN 2005
Totally corrective boosting algorithms that maximize the margin
ICML '06 Proceedings of the 23rd international conference on Machine learning
Ho-Kashyap classifier with early stopping for regularization
Pattern Recognition Letters
Kernel projection classifiers with suppressing features of other classes
Neural Computation
Support vector machines for dyadic data
Neural Computation
An analysis of diversity measures
Machine Learning
Efficient Margin Maximizing with Boosting
The Journal of Machine Learning Research
Variable selection in kernel Fisher discriminant analysis by means of recursive feature elimination
Computational Statistics & Data Analysis
Optimizing resources in model selection for support vector machine
Pattern Recognition
Using boosting to prune bagging ensembles
Pattern Recognition Letters
Parallelizing AdaBoost by weights dynamics
Computational Statistics & Data Analysis
Berlin Brain-Computer Interface-The HCI communication channel for discovery
International Journal of Human-Computer Studies
Kernel least-squares models using updates of the pseudoinverse
Neural Computation
Machine Learning
Computational Statistics & Data Analysis
Multi-Class Learning by Smoothed Boosting
Machine Learning
International Journal of Systems Science
The Journal of Machine Learning Research
Preventing Over-Fitting during Model Selection via Bayesian Regularisation of the Hyper-Parameters
The Journal of Machine Learning Research
Dimensionality Reduction of Multimodal Labeled Data by Local Fisher Discriminant Analysis
The Journal of Machine Learning Research
Robust Loss Functions for Boosting
Neural Computation
Increasing the Robustness of Boosting Algorithms within the Linear-programming Framework
Journal of VLSI Signal Processing Systems
Structured large margin machines: sensitive to data distributions
Machine Learning
Optimally regularised kernel Fisher discriminant classification
Neural Networks
Robust face detection in airports
EURASIP Journal on Applied Signal Processing
Boosting strategy for classification
Intelligent Data Analysis
A local boosting algorithm for solving classification problems
Computational Statistics & Data Analysis
Classifier learning with a new locality regularization method
Pattern Recognition
Classifier learning with a new locality regularization method
Pattern Recognition
An efficient modified boosting method for solving classification problems
Journal of Computational and Applied Mathematics
Improving relevance judgment of web search results with image excerpts
Proceedings of the 17th international conference on World Wide Web
Robust boosting algorithm against mislabeling in multiclass problems
Neural Computation
AdaBoost with SVM-based component classifiers
Engineering Applications of Artificial Intelligence
Stopping conditions for exact computation of leave-one-out error in support vector machines
Proceedings of the 25th international conference on Machine learning
Random classification noise defeats all convex potential boosters
Proceedings of the 25th international conference on Machine learning
Support Vector Machinery for Infinite Ensemble Learning
The Journal of Machine Learning Research
An Information Criterion for Variable Selection in Support Vector Machines
The Journal of Machine Learning Research
Hit Miss Networks with Applications to Instance Selection
The Journal of Machine Learning Research
Class-switching neural network ensembles
Neurocomputing
Parsimonious Kernel Fisher Discrimination
IbPRIA '07 Proceedings of the 3rd Iberian conference on Pattern Recognition and Image Analysis, Part I
Affine Feature Extraction: A Generalization of the Fukunaga-Koontz Transformation
MLDM '07 Proceedings of the 5th international conference on Machine Learning and Data Mining in Pattern Recognition
Efficient Implementation of SVM Training on Embedded Electronic Systems
WILF '07 Proceedings of the 7th international workshop on Fuzzy Logic and Applications: Applications of Fuzzy Sets Theory
HMM-Based Acoustic Event Detection with AdaBoost Feature Selection
Multimodal Technologies for Perception of Humans
ECML '07 Proceedings of the 18th European conference on Machine Learning
Learning Kernel Perceptrons on Noisy Data Using Random Projections
ALT '07 Proceedings of the 18th international conference on Algorithmic Learning Theory
Multiclass Boosting Algorithms for Shrinkage Estimators of Class Probability
ALT '07 Proceedings of the 18th international conference on Algorithmic Learning Theory
ANNPR '08 Proceedings of the 3rd IAPR workshop on Artificial Neural Networks in Pattern Recognition
A Kernel Method for the Optimization of the Margin Distribution
ICANN '08 Proceedings of the 18th international conference on Artificial Neural Networks, Part I
ICANN '08 Proceedings of the 18th international conference on Artificial Neural Networks, Part I
Uncertainty Handling in Model Selection for Support Vector Machines
Proceedings of the 10th international conference on Parallel Problem Solving from Nature: PPSN X
ALT '08 Proceedings of the 19th international conference on Algorithmic Learning Theory
Computers in Biology and Medicine
On Relevant Dimensions in Kernel Feature Spaces
The Journal of Machine Learning Research
International Journal of Systems Science
A support vector machine with integer parameters
Neurocomputing
Exploring Margin Maximization for Biometric Score Fusion
SSPR & SPR '08 Proceedings of the 2008 Joint IAPR International Workshop on Structural, Syntactic, and Statistical Pattern Recognition
Using Boosting to prune Double-Bagging ensembles
Computational Statistics & Data Analysis
Classification algorithm sensitivity to training data with non representative attribute noise
Decision Support Systems
Multiclass Boosting Algorithms for Shrinkage Estimators of Class Probability
IEICE - Transactions on Information and Systems
Boosting One-Class Support Vector Machines for Multi-Class Classification
Applied Artificial Intelligence
A wrapper method for feature selection using Support Vector Machines
Information Sciences: an International Journal
Classification of peptide mass fingerprint data by novel no-regret boosting method
Computers in Biology and Medicine
Negative correlation in incremental learning
Natural Computing: an international journal
Supervised projection approach for boosting classifiers
Pattern Recognition
Efficiently learning the accuracy of labeling sources for selective sampling
Proceedings of the 15th ACM SIGKDD international conference on Knowledge discovery and data mining
Validation-based sparse gaussian process classifier design
Neural Computation
Efficient AdaBoost Region Classification
MLDM '09 Proceedings of the 6th International Conference on Machine Learning and Data Mining in Pattern Recognition
Graph-Based Discrete Differential Geometry for Critical Instance Filtering
ECML PKDD '09 Proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases: Part II
Towards a Linear Combination of Dichotomizers by Margin Maximization
ICIAP '09 Proceedings of the 15th International Conference on Image Analysis and Processing
A Bayesian Kernel logistic discriminant model: an improvement to the Kernel Fisher's discriminant
AAAI'08 Proceedings of the 23rd national conference on Artificial intelligence - Volume 3
Boosting face identification in airports
IJCAI'03 Proceedings of the 18th international joint conference on Artificial intelligence
Learning a scene background model via classification
IEEE Transactions on Signal Processing
Construction of tunable radial basis function networks using orthogonal forward selection
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Fast support vector machines for continuous data
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics - Special issue on cybernetics and cognitive informatics
Multiclass classification based on extended support vector data description
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Fast and efficient strategies for model selection of Gaussian support vector machine
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Probabilistic classification vector machines
IEEE Transactions on Neural Networks
A novel geometric approach to binary classification based on scaled convex hulls
IEEE Transactions on Neural Networks
Processing of transcranial doppler for assessment of blood volume loss
IRI'09 Proceedings of the 10th IEEE international conference on Information Reuse & Integration
Feature Extraction Using Linear and Non-linear Subspace Techniques
ICANN '09 Proceedings of the 19th International Conference on Artificial Neural Networks: Part II
A rich feature vector for protein-protein interaction extraction from multiple corpora
EMNLP '09 Proceedings of the 2009 Conference on Empirical Methods in Natural Language Processing: Volume 1 - Volume 1
Subspace based linear programming support vector machines
IJCNN'09 Proceedings of the 2009 international joint conference on Neural Networks
Subspace based least squares support vector machines for pattern classification
IJCNN'09 Proceedings of the 2009 international joint conference on Neural Networks
Sparse kernel feature analysis using FastMap and its variants
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
Evolutionary tuning of multiple SVM parameters
Neurocomputing
Boosting by weighting critical and erroneous samples
Neurocomputing
Switching class labels to generate classification ensembles
Pattern Recognition
Optimized fixed-size kernel models for large data sets
Computational Statistics & Data Analysis
A Least-squares Approach to Direct Importance Estimation
The Journal of Machine Learning Research
Maximum Relative Margin and Data-Dependent Regularization
The Journal of Machine Learning Research
Averaged boosting: a noise-robust ensemble method
PAKDD'03 Proceedings of the 7th Pacific-Asia conference on Advances in knowledge discovery and data mining
Improving performance of a multiple classifier system using self-generating neural networks
MCS'03 Proceedings of the 4th international conference on Multiple classifier systems
Machine learning and applications for brain-computer interfacing
Proceedings of the 2007 conference on Human interface: Part I
Effective pruning method for a multiple classifier system based on self-generating neural networks
ICANN/ICONIP'03 Proceedings of the 2003 joint international conference on Artificial neural networks and neural information processing
Analysis of the distance between two classes for tuning SVM hyperparameters
IEEE Transactions on Neural Networks
Combining image, voice, and the patient's questionnaire data to categorize laryngeal disorders
Artificial Intelligence in Medicine
On selection and combination of weak learners in AdaBoost
Pattern Recognition Letters
A novel multi-stage classifier for face recognition
ACCV'07 Proceedings of the 8th Asian conference on Computer vision - Volume Part II
Resilient approximation of kernel classifiers
ICANN'07 Proceedings of the 17th international conference on Artificial neural networks
Sparse kernel modelling: a unified approach
IDEAL'07 Proceedings of the 8th international conference on Intelligent data engineering and automated learning
Improving boosting by exploiting former assumptions
MCD'07 Proceedings of the 3rd ECML/PKDD international conference on Mining complex data
Semi-supervised local fisher discriminant analysis for dimensionality reduction
PAKDD'08 Proceedings of the 12th Pacific-Asia conference on Advances in knowledge discovery and data mining
Tuning SVM parameters by using a hybrid CLPSO-BFGS algorithm
Neurocomputing
Efficient learning and feature selection in high-dimensional regression
Neural Computation
Boosting through optimization of margin distributions
IEEE Transactions on Neural Networks
Novel maximum-margin training algorithms for supervised neural networks
IEEE Transactions on Neural Networks
Real-world acoustic event detection
Pattern Recognition Letters
Learning Translation Invariant Kernels for Classification
The Journal of Machine Learning Research
On Over-fitting in Model Selection and Subsequent Selection Bias in Performance Evaluation
The Journal of Machine Learning Research
Particle swarm optimization aided orthogonal forward regression for unified data modeling
IEEE Transactions on Evolutionary Computation
Edited AdaBoost by weighted kNN
Neurocomputing
Simultaneous feature selection and classification using kernel-penalized support vector machines
Information Sciences: an International Journal
Object of interest detection by saliency learning
ECCV'10 Proceedings of the 11th European conference on Computer vision: Part II
Emotion recognition from arbitrary view facial images
ECCV'10 Proceedings of the 11th European conference on Computer vision: Part VI
Learning with ensembles of randomized trees: new insights
ECML PKDD'10 Proceedings of the 2010 European conference on Machine learning and knowledge discovery in databases: Part III
Approximation stability and boosting
ALT'10 Proceedings of the 21st international conference on Algorithmic learning theory
Feature extraction using support vector machines
ICONIP'10 Proceedings of the 17th international conference on Neural information processing: models and applications - Volume Part II
Hubs in Space: Popular Nearest Neighbors in High-Dimensional Data
The Journal of Machine Learning Research
Bayesian Generalized Kernel Mixed Models
The Journal of Machine Learning Research
S-adaboost and pattern detection in complex environment
CVPR'03 Proceedings of the 2003 IEEE computer society conference on Computer vision and pattern recognition
ICCOMP'06 Proceedings of the 10th WSEAS international conference on Computers
The LCCP for optimizing kernel parameters for SVM
ICANN'05 Proceedings of the 15th international conference on Artificial neural networks: formal models and their applications - Volume Part II
Interpretable visual models for human perception-based object retrieval
Proceedings of the 1st ACM International Conference on Multimedia Retrieval
Neural Networks
Online heterogeneous mixture modeling with marginal and copula selection
Proceedings of the 17th ACM SIGKDD international conference on Knowledge discovery and data mining
A computationally efficient information estimator for weighted data
ICANN'11 Proceedings of the 21st international conference on Artificial neural networks - Volume Part II
A novel SVM+NDA model for classification with an application to face recognition
Pattern Recognition
Cloosting: clustering data with boosting
MCS'11 Proceedings of the 10th international conference on Multiple classifier systems
Exploring cascade classifiers for detecting clusters of microcalcifications
ICIAP'11 Proceedings of the 16th international conference on Image analysis and processing: Part I
On Equivalence Relationships Between Classification and Ranking Algorithms
The Journal of Machine Learning Research
A weighting initialization strategy for weighted support vector machines
ICAPR'05 Proceedings of the Third international conference on Advances in Pattern Recognition - Volume Part I
ICAPR'05 Proceedings of the Third international conference on Advances in Pattern Recognition - Volume Part I
Model selection in kernel methods based on a spectral analysis of label information
DAGM'06 Proceedings of the 28th conference on Pattern Recognition
PSO-Based hyper-parameters selection for LS-SVM classifiers
ICONIP'06 Proceedings of the 13th international conference on Neural Information Processing - Volume Part II
Fast variational inference for gaussian process models through KL-Correction
ECML'06 Proceedings of the 17th European conference on Machine Learning
SOM-based novelty detection using novel data
IDEAL'05 Proceedings of the 6th international conference on Intelligent Data Engineering and Automated Learning
A new pre-processing method for regression
ISNN'06 Proceedings of the Third international conference on Advnaces in Neural Networks - Volume Part II
Relevance vector machine based infinite decision agent ensemble learning for credit risk analysis
Expert Systems with Applications: An International Journal
ICIC'06 Proceedings of the 2006 international conference on Intelligent Computing - Volume Part I
A modular reduction method for k-NN algorithm with self-recombination learning
ISNN'06 Proceedings of the Third international conference on Advances in Neural Networks - Volume Part I
Selective neural network ensemble based on clustering
ISNN'06 Proceedings of the Third international conference on Advances in Neural Networks - Volume Part I
Building ensembles of neural networks with class-switching
ICANN'06 Proceedings of the 16th international conference on Artificial Neural Networks - Volume Part I
Nature inspiration for support vector machines
KES'06 Proceedings of the 10th international conference on Knowledge-Based Intelligent Information and Engineering Systems - Volume Part II
Infinite ensemble learning with support vector machines
ECML'05 Proceedings of the 16th European conference on Machine Learning
ECML'05 Proceedings of the 16th European conference on Machine Learning
Multi-objective model selection for support vector machines
EMO'05 Proceedings of the Third international conference on Evolutionary Multi-Criterion Optimization
Learning outliers to refine a corpus for chinese webpage categorization
ICNC'05 Proceedings of the First international conference on Advances in Natural Computation - Volume Part I
COLT'05 Proceedings of the 18th annual conference on Learning Theory
Incorporating geometry information with weak classifiers for improved generic visual categorization
ICIAP'05 Proceedings of the 13th international conference on Image Analysis and Processing
Machine learning on historic air photographs for mapping risk of unexploded bombs
ICIAP'05 Proceedings of the 13th international conference on Image Analysis and Processing
Short communication: On estimating simple probabilistic discriminative models with subclasses
Expert Systems with Applications: An International Journal
Hard margin SVM for biomedical image segmentation
ISNN'05 Proceedings of the Second international conference on Advances in Neural Networks - Volume Part III
Feature selection using SVM probabilistic outputs
ICONIP'06 Proceedings of the 13 international conference on Neural Information Processing - Volume Part I
A face cartoon producer for digital content service
Mobile Multimedia Processing
A new SVM + NDA model for improved classification and recognition
ICIAR'10 Proceedings of the 7th international conference on Image Analysis and Recognition - Volume Part I
Multiple kernel learning with gaussianity measures
Neural Computation
Probit classifiers with a generalized Gaussian scale mixture prior
IJCAI'11 Proceedings of the Twenty-Second international joint conference on Artificial Intelligence - Volume Volume Two
Nyström approximate model selection for LSSVM
PAKDD'12 Proceedings of the 16th Pacific-Asia conference on Advances in Knowledge Discovery and Data Mining - Volume Part I
A noise-detection based AdaBoost algorithm for mislabeled data
Pattern Recognition
RSGALS-SVM: random subspace method applied to a LS-SVM ensemble optimized by genetic algorithm
IDEAL'12 Proceedings of the 13th international conference on Intelligent Data Engineering and Automated Learning
A robust adaboost-based algorithm for low-resolution face detection
IDEAL'12 Proceedings of the 13th international conference on Intelligent Data Engineering and Automated Learning
Probabilistic classifiers with a generalized Gaussian scale mixture prior
Pattern Recognition
Random subspace method and genetic algorithm applied to a LS-SVM ensemble
ICANN'12 Proceedings of the 22nd international conference on Artificial Neural Networks and Machine Learning - Volume Part II
A sparse support vector machine classifier with nonparametric discriminants
ICANN'12 Proceedings of the 22nd international conference on Artificial Neural Networks and Machine Learning - Volume Part II
Change detection based on a support vector data description that treats dependency
Pattern Recognition Letters
A novel method of sparse least squares support vector machines in class empirical feature space
ICONIP'12 Proceedings of the 19th international conference on Neural Information Processing - Volume Part II
A unified classification model based on robust optimization
Neural Computation
Adaptive object detection by implicit sub-class sharing features
Signal Processing
Reducing overfitting of AdaBoost by clustering-based pruning of hard examples
Proceedings of the 7th International Conference on Ubiquitous Information Management and Communication
Semi-supervised learning with density-ratio estimation
Machine Learning
Smoothed emphasis for boosting ensembles
IWANN'13 Proceedings of the 12th international conference on Artificial Neural Networks: advances in computational intelligence - Volume Part I
Robust predictive model for evaluating breast cancer survivability
Engineering Applications of Artificial Intelligence
Information estimators for weighted observations
Neural Networks
Active learning for noisy oracle via density power divergence
Neural Networks
On the doubt about margin explanation of boosting
Artificial Intelligence
Evaluation of sampling methods for learning from imbalanced data
ICIC'13 Proceedings of the 9th international conference on Intelligent Computing Theories
The C-loss function for pattern classification
Pattern Recognition
Fully corrective boosting with arbitrary loss and regularization
Neural Networks
A nested heuristic for parameter tuning in Support Vector Machines
Computers and Operations Research
Conjugate relation between loss functions and uncertainty sets in classification problems
The Journal of Machine Learning Research
The rate of convergence of AdaBoost
The Journal of Machine Learning Research
| Hi-index | 0.01 |
Recently ensemble methods like ADABOOST have been applied successfully in many problems, while seemingly defying the problems of overfitting.ADABOOST rarely overfits in the low noise regime, however, we show that it clearly does so for higher noise levels. Central to the understanding of this fact is the margin distribution. ADABOOST can be viewed as a constraint gradient descent in an error function with respect to the margin. We find that ADABOOST asymptotically achieves a hard margin distribution, i.e. the algorithm concentrates its resources on a few hard-to-learn patterns that are interestingly very similar to Support Vectors. A hard margin is clearly a sub-optimal strategy in the noisy case, and regularization, in our case a “mistrust” in the data, must be introduced in the algorithm to alleviate the distortions that single difficult patterns (e.g. outliers) can cause to the margin distribution. We propose several regularization methods and generalizations of the original ADABOOST algorithm to achieve a soft margin. In particular we suggest (1) regularized ADABOOSTREG where the gradient decent is done directly with respect to the soft margin and (2) regularized linear and quadratic programming (LP/QP-) ADABOOST, where the soft margin is attained by introducing slack variables.Extensive simulations demonstrate that the proposed regularized ADABOOST-type algorithms are useful and yield competitive results for noisy data.