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ACM SIGKDD Explorations Newsletter - Special issue on “Scalable data mining algorithms”
Proximal support vector machine classifiers
Proceedings of the seventh ACM SIGKDD international conference on Knowledge discovery and data mining
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Editorial: Kernel Methods: Current Research and Future Directions
Machine Learning
MARK: a boosting algorithm for heterogeneous kernel models
Proceedings of the eighth ACM SIGKDD international conference on Knowledge discovery and data mining
Cancer classification using gene expression data
Information Systems - Special issue: Data management in bioinformatics
A short introduction to learning with kernels
Advanced lectures on machine learning
Regularized principal manifolds
The Journal of Machine Learning Research
Introduction to the special issue on kernel methods
The Journal of Machine Learning Research
The Journal of Machine Learning Research
Grafting: fast, incremental feature selection by gradient descent in function space
The Journal of Machine Learning Research
Kernel VA-files for relevance feedback retrieva
MMDB '03 Proceedings of the 1st ACM international workshop on Multimedia databases
Various hyperplane classifiers using kernel feature spaces
Acta Cybernetica
Generalization Error Bounds for Threshold Decision Lists
The Journal of Machine Learning Research
Learning large margin classifiers locally and globally
ICML '04 Proceedings of the twenty-first international conference on Machine learning
A theoretical characterization of linear SVM-based feature selection
ICML '04 Proceedings of the twenty-first international conference on Machine learning
An asymptotic statistical theory of polynomial kernel methods
Neural Computation
Extracting word sequence correspondences with support vector machines
COLING '02 Proceedings of the 19th international conference on Computational linguistics - Volume 1
The cross entropy method for classification
ICML '05 Proceedings of the 22nd international conference on Machine learning
ICDM '05 Proceedings of the Fifth IEEE International Conference on Data Mining
Geometrical Properties of Nu Support Vector Machines with Different Norms
Neural Computation
Different Paradigms for Choosing Sequential Reweighting Algorithms
Neural Computation
On a theory of learning with similarity functions
ICML '06 Proceedings of the 23rd international conference on Machine learning
Practical solutions to the problem of diagonal dominance in kernel document clustering
ICML '06 Proceedings of the 23rd international conference on Machine learning
Knowledge and Information Systems - Special Issue on Mining Low-Quality Data
Optimizing combustion efficiency of a circulating fluidized boiler: A data mining approach
International Journal of Knowledge-based and Intelligent Engineering Systems - Selected papers from the KES2004 conference
On the generalization error of fixed combinations of classifiers
Journal of Computer and System Sciences
A support vector method for optimizing average precision
SIGIR '07 Proceedings of the 30th annual international ACM SIGIR conference on Research and development in information retrieval
Structured large margin machines: sensitive to data distributions
Machine Learning
Classification-based spatial error concealment for visual communications
EURASIP Journal on Applied Signal Processing
Support vector fuzzy adaptive network in regression analysis
Computers & Mathematics with Applications
epsilon-Support Vector and Large-Scale Data Mining Problems
ICCS '07 Proceedings of the 7th international conference on Computational Science, Part III: ICCS 2007
Entropy-based associative classification algorithm for mining manufacturing data
International Journal of Computer Integrated Manufacturing
Semi-supervised classification using local and global regularization
AAAI'08 Proceedings of the 23rd national conference on Artificial intelligence - Volume 2
CEC'09 Proceedings of the Eleventh conference on Congress on Evolutionary Computation
A3CRank: An adaptive ranking method based on connectivity, content and click-through data
Information Processing and Management: an International Journal
Generalization error analysis for polynomial kernel methods: algebraic geometrical approach
ICANN/ICONIP'03 Proceedings of the 2003 joint international conference on Artificial neural networks and neural information processing
Discriminative training of HMMs for automatic speech recognition: A survey
Computer Speech and Language
A general learning framework using local and global regularization
Pattern Recognition
A support vector machine with forgetting factor and its statistical properties
ICONIP'08 Proceedings of the 15th international conference on Advances in neuro-information processing - Volume Part I
Complex feature alternating decision tree
International Journal of Intelligent Systems Technologies and Applications
Class information adapted kernel for support vector machine
ICONIP'10 Proceedings of the 17th international conference on Neural information processing: models and applications - Volume Part II
Tensor-based locally maximum margin classifier for image and video classification
Computer Vision and Image Understanding
Effective probability forecasting for time series data using standard machine learning techniques
ICAPR'05 Proceedings of the Third international conference on Advances in Pattern Recognition - Volume Part I
A comparative study on the use of labeled and unlabeled data for large margin classifiers
IJCNLP'04 Proceedings of the First international joint conference on Natural Language Processing
Stock index prediction based on the analytical center of version space
ISNN'06 Proceedings of the Third international conference on Advances in Neural Networks - Volume Part III
Robust cutpoints in the logical analysis of numerical data
Discrete Applied Mathematics
Manifold embedding of graphs using the heat kernel
IMA'05 Proceedings of the 11th IMA international conference on Mathematics of Surfaces
A multiclass classification framework for document categorization
DAS'06 Proceedings of the 7th international conference on Document Analysis Systems
Enhanced default risk models with SVM+
Expert Systems with Applications: An International Journal
Entity linking with effective acronym expansion, instance selection and topic modeling
IJCAI'11 Proceedings of the Twenty-Second international joint conference on Artificial Intelligence - Volume Volume Three
Efficient optimization for low-rank integrated bilinear classifiers
ECCV'12 Proceedings of the 12th European conference on Computer Vision - Volume Part II
Predicting content change on the web
Proceedings of the sixth ACM international conference on Web search and data mining
New empirical nonparametric kernels for support vector machine classification
Applied Soft Computing
Bubble space and place representation in topological maps
International Journal of Robotics Research
Large margin principle in hyperrectangle learning
Neurocomputing
Learning bounds via sample width for classifiers on finite metric spaces
Theoretical Computer Science
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From the Publisher:The concept of large margins is a unifying principle for the analysis of many different approaches to the classification of data from examples, including boosting, mathematical programming, neural networks, and support vector machines. The fact that it is the margin, or confidence level, of a classification--that is, a scale parameter--rather than a raw training error that matters has become a key tool for dealing with classifiers. This book shows how this idea applies to both the theoretical analysis and the design of algorithms. The book provides an overview of recent developments in large margin classifiers, examines connections with other methods (e.g., Bayesian inference), and identifies strengths and weaknesses of the method, as well as directions for future research. Among the contributors are Manfred Opper, Vladimir Vapnik, and Grace Wahba.