Communications of the ACM
Information Processing Letters
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
On the convergence of the coordinate descent method for convex differentiable minimization
Journal of Optimization Theory and Applications
C4.5: programs for machine learning
C4.5: programs for machine learning
Decision theoretic generalizations of the PAC model for neural net and other learning applications
Information and Computation
Cryptographic limitations on learning Boolean formulae and finite automata
Journal of the ACM (JACM)
Hierarchical mixtures of experts and the EM algorithm
Neural Computation
Stable exponential-penalty algorithm with superlinear convergence
Journal of Optimization Theory and Applications
An introduction to computational learning theory
An introduction to computational learning theory
The nature of statistical learning theory
The nature of statistical learning theory
On-line learning of linear functions
Computational Complexity
Machine Learning
Boosting a weak learning algorithm by majority
Information and Computation
Machine Learning
On the boosting ability of top-down decision tree learning algorithms
STOC '96 Proceedings of the twenty-eighth annual ACM symposium on Theory of computing
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
Exponentiated gradient versus gradient descent for linear predictors
Information and Computation
A decision-theoretic generalization of on-line learning and an application to boosting
Journal of Computer and System Sciences - Special issue: 26th annual ACM symposium on the theory of computing & STOC'94, May 23–25, 1994, and second annual Europe an conference on computational learning theory (EuroCOLT'95), March 13–15, 1995
Artificial Intelligence - Special issue on relevance
Improved boosting algorithms using confidence-rated predictions
COLT' 98 Proceedings of the eleventh annual conference on Computational learning theory
Boosting and Rocchio applied to text filtering
Proceedings of the 21st annual international ACM SIGIR conference on Research and development in information retrieval
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
NIPS '97 Proceedings of the 1997 conference on Advances in neural information processing systems 10
Additive models, boosting, and inference for generalized divergences
COLT '99 Proceedings of the twelfth annual conference on Computational learning theory
Boosting as entropy projection
COLT '99 Proceedings of the twelfth annual conference on Computational learning theory
Multiclass learning, boosting, and error-correcting codes
COLT '99 Proceedings of the twelfth annual conference on Computational learning theory
Further results on the margin distribution
COLT '99 Proceedings of the twelfth annual conference on Computational learning theory
Using Decision Trees to Construct a Practical Parser
Machine Learning - Special issue on natural language learning
Prediction games and arcing algorithms
Neural Computation
Classification on pairwise proximity data
Proceedings of the 1998 conference on Advances in neural information processing systems II
An introduction to support Vector Machines: and other kernel-based learning methods
An introduction to support Vector Machines: and other kernel-based learning methods
BoosTexter: A Boosting-based Systemfor Text Categorization
Machine Learning - Special issue on information retrieval
Proceedings of the ninth international conference on Information and knowledge management
Machine Learning
Experimental comparisons of online and batch versions of bagging and boosting
Proceedings of the seventh ACM SIGKDD international conference on Knowledge discovery and data mining
AI Game Programming Wisdom
Neural Networks: A Comprehensive Foundation
Neural Networks: A Comprehensive Foundation
Neural Networks for Pattern Recognition
Neural Networks for Pattern Recognition
Parallel Optimization: Theory, Algorithms and Applications
Parallel Optimization: Theory, Algorithms and Applications
Learning in Neural Networks: Theoretical Foundations
Learning in Neural Networks: Theoretical Foundations
On Bias, Variance, 0/1—Loss, and the Curse-of-Dimensionality
Data Mining and Knowledge Discovery
An Adaptive Version of the Boost by Majority Algorithm
Machine Learning
Linear Programming Boosting via Column Generation
Machine Learning
Choosing Multiple Parameters for Support Vector Machines
Machine Learning
Model Selection and Error Estimation
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
ECML '02 Proceedings of the 13th European Conference on Machine Learning
ECML '02 Proceedings of the 13th European Conference on Machine Learning
Some Theoretical Aspects of Boosting in the Presence of Noisy Data
ICML '01 Proceedings of the Eighteenth International Conference on Machine Learning
Modeling Auction Price Uncertainty Using Boosting-based Conditional Density Estimation
ICML '02 Proceedings of the Nineteenth International Conference on Machine Learning
Using output codes to boost multiclass learning problems
ICML '97 Proceedings of the Fourteenth International Conference on Machine Learning
Feature Selection via Concave Minimization and Support Vector Machines
ICML '98 Proceedings of the Fifteenth International Conference on Machine Learning
FeatureBoost: A Meta-Learning Algorithm that Improves Model Robustness
ICML '00 Proceedings of the Seventeenth International Conference on Machine Learning
A Boosting Algorithm for Regression
ICANN '97 Proceedings of the 7th International Conference on Artificial Neural Networks
A Brief Introduction to Boosting
IJCAI '99 Proceedings of the Sixteenth International Joint Conference on Artificial Intelligence
Improving Algorithms for Boosting
COLT '00 Proceedings of the Thirteenth Annual Conference on Computational Learning Theory
Sparsity vs. Large Margins for Linear Classifiers
COLT '00 Proceedings of the Thirteenth Annual Conference on Computational Learning Theory
On the Learnability and Design of Output Codes for Multiclass Problems
COLT '00 Proceedings of the Thirteenth Annual Conference on Computational Learning Theory
PAC Analogues of Perceptron and Winnow via Boosting the Margin
COLT '00 Proceedings of the Thirteenth Annual Conference on Computational Learning Theory
MadaBoost: A Modification of AdaBoost
COLT '00 Proceedings of the Thirteenth Annual 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
COLT '00 Proceedings of the Thirteenth Annual Conference on Computational Learning Theory
The Consistency of Greedy Algorithms for Classification
COLT '02 Proceedings of the 15th Annual Conference on Computational Learning Theory
Maximizing the Margin with Boosting
COLT '02 Proceedings of the 15th Annual Conference on Computational Learning Theory
A Consistent Strategy for Boosting Algorithms
COLT '02 Proceedings of the 15th Annual Conference on Computational Learning Theory
Localized Rademacher Complexities
COLT '02 Proceedings of the 15th Annual Conference on Computational Learning Theory
An Efficient Boosting Algorithm for Combining Preferences
ICML '98 Proceedings of the Fifteenth International Conference on Machine Learning
ALT '96 Proceedings of the 7th International Workshop on Algorithmic Learning Theory
Boosting Density Function Estimators
ECML '02 Proceedings of the 13th European Conference on Machine Learning
ICML '01 Proceedings of the Eighteenth International Conference on Machine Learning
Exploiting unlabeled data in ensemble methods
Proceedings of the eighth ACM SIGKDD international conference on Knowledge discovery and data mining
Pose Invariant Face Recognition
FG '00 Proceedings of the Fourth IEEE International Conference on Automatic Face and Gesture Recognition 2000
Reducing multiclass to binary: a unifying approach for margin classifiers
The Journal of Machine Learning Research
Data-dependent margin-based generalization bounds for classification
The Journal of Machine Learning Research
The Journal of Machine Learning Research
Rademacher and gaussian complexities: risk bounds and structural results
The Journal of Machine Learning Research
On boosting with polynomially bounded distributions
The Journal of Machine Learning Research
SPoT: a trainable sentence planner
NAACL '01 Proceedings of the second meeting of the North American Chapter of the Association for Computational Linguistics on Language technologies
Neural Computation
Neural Computation
Solving multiclass learning problems via error-correcting output codes
Journal of Artificial Intelligence Research
Lung cancer cell identification based on artificial neural network ensembles
Artificial Intelligence in Medicine
Structural risk minimization over data-dependent hierarchies
IEEE Transactions on Information Theory
Relative loss bounds for single neurons
IEEE Transactions on Neural Networks
An introduction to kernel-based learning algorithms
IEEE Transactions on Neural Networks
Subspace information criterion for nonquadratic regularizers-Model selection for sparse regressors
IEEE Transactions on Neural Networks
Greedy algorithms for classification—consistency, convergence rates, and adaptivity
The Journal of Machine Learning Research
On the rate of convergence of regularized boosting classifiers
The Journal of Machine Learning Research
Web taxonomy integration through co-bootstrapping
Proceedings of the 27th annual international ACM SIGIR conference on Research and development in information retrieval
Automated Protein Classification Using Consensus Decision
CSB '04 Proceedings of the 2004 IEEE Computational Systems Bioinformatics Conference
The Dynamics of AdaBoost: Cyclic Behavior and Convergence of Margins
The Journal of Machine Learning Research
Coevolutionary feature synthesized EM algorithm for image retrieval
Proceedings of the 13th annual ACM international conference on Multimedia
Different Paradigms for Choosing Sequential Reweighting Algorithms
Neural Computation
How boosting the margin can also boost classifier complexity
ICML '06 Proceedings of the 23rd international conference on Machine learning
Learning the unified kernel machines for classification
Proceedings of the 12th ACM SIGKDD international conference on Knowledge discovery and data mining
Identifying and classifying subjective claims
dg.o '07 Proceedings of the 8th annual international conference on Digital government research: bridging disciplines & domains
Large Scale Multiple Kernel Learning
The Journal of Machine Learning Research
Concave Learners for Rankboost
The Journal of Machine Learning Research
Increasing the Robustness of Boosting Algorithms within the Linear-programming Framework
Journal of VLSI Signal Processing Systems
Information acquisition using multiple classifications
Proceedings of the 4th international conference on Knowledge capture
Autonomously semantifying wikipedia
Proceedings of the sixteenth ACM conference on Conference on information and knowledge management
An efficient modified boosting method for solving classification problems
Journal of Computational and Applied Mathematics
Feature synthesized EM algorithm for image retrieval
ACM Transactions on Multimedia Computing, Communications, and Applications (TOMCCAP)
The value of agreement a new boosting algorithm
Journal of Computer and System Sciences
Content based video matching using spatiotemporal volumes
Computer Vision and Image Understanding
RotBoost: A technique for combining Rotation Forest and AdaBoost
Pattern Recognition Letters
Covariate Shift Adaptation by Importance Weighted Cross Validation
The Journal of Machine Learning Research
Support Vector Machinery for Infinite Ensemble Learning
The Journal of Machine Learning Research
Semi-supervised sub-manifold discriminant analysis
Pattern Recognition Letters
Boosting Descriptive ILP for Predictive Learning in Bioinformatics
Inductive Logic Programming
From Ensemble of Fuzzy Classifiers to Single Fuzzy Rule Base Classifier
ICAISC '08 Proceedings of the 9th international conference on Artificial Intelligence and Soft Computing
Evolutionary Methods to Create Interpretable Modular System
ICAISC '08 Proceedings of the 9th international conference on Artificial Intelligence and Soft Computing
Patient-centered yes/no prognosis using learning machines
International Journal of Data Mining and Bioinformatics
Prototype classification: Insights from machine learning
Neural Computation
Boosting with structural sparsity
ICML '09 Proceedings of the 26th Annual International Conference on Machine Learning
A novel method for constructing ensemble classifiers
Statistics and Computing
Activity recognition from accelerometer data
IAAI'05 Proceedings of the 17th conference on Innovative applications of artificial intelligence - Volume 3
Managing domain knowledge and multiple models with boosting
IJCAI'07 Proceedings of the 20th international joint conference on Artifical intelligence
Pattern recognition techniques for automatic detection of suspicious-looking anomalies in mammograms
Computer Methods and Programs in Biomedicine
Boosting Classifiers Built from Different Subsets of Features
Fundamenta Informaticae
Neuro-fuzzy Rough Classifier Ensemble
ICANN '09 Proceedings of the 19th International Conference on Artificial Neural Networks: Part I
Boosting with a Joint Feature Pool from Different Sensors
ICVS '09 Proceedings of the 7th International Conference on Computer Vision Systems: Computer Vision Systems
Learning to integrate web taxonomies
Web Semantics: Science, Services and Agents on the World Wide Web
Boosting by weighting critical and erroneous samples
Neurocomputing
ViSOM ensembles for visualization and classification
IWANN'07 Proceedings of the 9th international work conference on Artificial neural networks
Quality of adaptation of fusion ViSOM
IDEAL'07 Proceedings of the 8th international conference on Intelligent data engineering and automated learning
Modular rough neuro-fuzzy systems for classification
PPAM'07 Proceedings of the 7th international conference on Parallel processing and applied mathematics
Modular type-2 neuro-fuzzy systems
PPAM'07 Proceedings of the 7th international conference on Parallel processing and applied mathematics
Boosting through optimization of margin distributions
IEEE Transactions on Neural Networks
Probability density estimation with tunable kernels using orthogonal forward regression
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics - Special issue on gait analysis
Information extraction from concise passages of natural language sources
ADBIS'10 Proceedings of the 14th east European conference on Advances in databases and information systems
Surrogate modeling approximation using a mixture of experts based on EM joint estimation
Structural and Multidisciplinary Optimization
AdaBoost classifiers for pecan defect classification
Computers and Electronics in Agriculture
A Refined Margin Analysis for Boosting Algorithms via Equilibrium Margin
The Journal of Machine Learning Research
Adaboost ensemble of DCOG rough-neuro-fuzzy systems
ICCCI'11 Proceedings of the Third international conference on Computational collective intelligence: technologies and applications - Volume Part I
AdaBoost-based approach for detecting lithiasis and polyps in USG images of the gallbladder
IVIC'11 Proceedings of the Second international conference on Visual informatics: sustaining research and innovations - Volume Part I
A search algorithm for global optimisation
ICNC'05 Proceedings of the First international conference on Advances in Natural Computation - Volume Part II
Two-Stage classifier for diagnosis of hypertension type
ISBMDA'06 Proceedings of the 7th international conference on Biological and Medical Data Analysis
Solving semi-infinite linear programs using boosting-like methods
ALT'06 Proceedings of the 17th international conference on Algorithmic Learning Theory
Large-Margin thresholded ensembles for ordinal regression: theory and practice
ALT'06 Proceedings of the 17th international conference on Algorithmic Learning Theory
Cascade evaluation of clustering algorithms
ECML'06 Proceedings of the 17th European conference on Machine Learning
Boosting for text classification with semantic features
WebKDD'04 Proceedings of the 6th international conference on Knowledge Discovery on the Web: advances in Web Mining and Web Usage Analysis
MP-Boost: a multiple-pivot boosting algorithm and its application to text categorization
SPIRE'06 Proceedings of the 13th international conference on String Processing and Information Retrieval
Infinite ensemble learning with support vector machines
ECML'05 Proceedings of the 16th European conference on Machine Learning
The value of agreement, a new boosting algorithm
COLT'05 Proceedings of the 18th annual conference on Learning Theory
Learning the bias of a classifier in a GA-Based inductive learning environment
ICIC'05 Proceedings of the 2005 international conference on Advances in Intelligent Computing - Volume Part I
IDA'05 Proceedings of the 6th international conference on Advances in Intelligent Data Analysis
Combining logical-type neuro-fuzzy systems
ICAISC'06 Proceedings of the 8th international conference on Artificial Intelligence and Soft Computing
Boosting ensemble of relational neuro-fuzzy systems
ICAISC'06 Proceedings of the 8th international conference on Artificial Intelligence and Soft Computing
Boosting GARCH and neural networks for the prediction of heteroskedastic time series
Mathematical and Computer Modelling: An International Journal
A boosting approach for supervised Mahalanobis distance metric learning
Pattern Recognition
Pattern Recognition Letters
A survey of cost-sensitive decision tree induction algorithms
ACM Computing Surveys (CSUR)
Variable-constraint classification and quantification of radiology reports under the ACR Index
Expert Systems with Applications: An International Journal
Quantum adiabatic machine learning
Quantum Information Processing
Local descriptors and similarity measures for frontal face recognition: A comparative analysis
Journal of Visual Communication and Image Representation
Fully corrective boosting with arbitrary loss and regularization
Neural Networks
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We provide an introduction to theoretical and practical aspects of Boosting and Ensemble learning, providing a useful reference for researchers in the field of Boosting as well as for those seeking to enter this fascinating area of research. We begin with a short background concerning the necessary learning theoretical foundations of weak learners and their linear combinations. We then point out the useful connection between Boosting and the Theory of Optimization, which facilitates the understanding of Boosting and later on enables us to move on to new Boosting algorithms, applicable to a broad spectrum of problems. In order to increase the relevance of the paper to practitioners, we have added remarks, pseudo code, "tricks of the trade", and algorithmic considerations where appropriate. Finally, we illustrate the usefulness of Boosting algorithms by giving an overview of some existing applications. The main ideas are illustrated on the problem of binary classification, although several extensions are discussed.