Neural Computation
Local algorithms for pattern recognition and dependencies estimation
Neural Computation
An introduction to computational learning theory
An introduction to computational learning theory
The nature of statistical learning theory
The nature of statistical learning theory
Machine learning, neural and statistical classification
Machine learning, neural and statistical classification
Machine Learning
Machine Learning
Artificial Intelligence Review - Special issue on lazy learning
Nearest neighbor queries in metric spaces
STOC '97 Proceedings of the twenty-ninth annual ACM symposium on Theory of computing
Lazy learning
Making large-scale support vector machine learning practical
Advances in kernel methods
Pairwise classification and support vector machines
Advances in kernel methods
Learning with Kernels: Support Vector Machines, Regularization, Optimization, and Beyond
Learning with Kernels: Support Vector Machines, Regularization, Optimization, and Beyond
Computers and Intractability: A Guide to the Theory of NP-Completeness
Computers and Intractability: A Guide to the Theory of NP-Completeness
Neural Computation
Reducing multiclass to binary: a unifying approach for margin classifiers
The Journal of Machine Learning Research
The Journal of Machine Learning Research
Navigating nets: simple algorithms for proximity search
SODA '04 Proceedings of the fifteenth annual ACM-SIAM symposium on Discrete algorithms
Fast SVM Training Algorithm with Decomposition on Very Large Data Sets
IEEE Transactions on Pattern Analysis and Machine Intelligence
Core Vector Machines: Fast SVM Training on Very Large Data Sets
The Journal of Machine Learning Research
A Modified Finite Newton Method for Fast Solution of Large Scale Linear SVMs
The Journal of Machine Learning Research
Cover trees for nearest neighbor
ICML '06 Proceedings of the 23rd international conference on Machine learning
Trading convexity for scalability
ICML '06 Proceedings of the 23rd international conference on Machine learning
Training linear SVMs in linear time
Proceedings of the 12th ACM SIGKDD international conference on Knowledge discovery and data mining
SVM-KNN: Discriminative Nearest Neighbor Classification for Visual Category Recognition
CVPR '06 Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 2
A Minimum Sphere Covering Approach to Pattern Classification
ICPR '06 Proceedings of the 18th International Conference on Pattern Recognition - Volume 03
Fast Kernel Classifiers with Online and Active Learning
The Journal of Machine Learning Research
Working Set Selection Using Second Order Information for Training Support Vector Machines
The Journal of Machine Learning Research
Statistical Comparisons of Classifiers over Multiple Data Sets
The Journal of Machine Learning Research
Parallel Software for Training Large Scale Support Vector Machines on Multiprocessor Systems
The Journal of Machine Learning Research
Building Support Vector Machines with Reduced Classifier Complexity
The Journal of Machine Learning Research
Comments on the "Core Vector Machines: Fast SVM Training on Very Large Data Sets"
The Journal of Machine Learning Research
Trust region Newton methods for large-scale logistic regression
Proceedings of the 24th international conference on Machine learning
Pegasos: Primal Estimated sub-GrAdient SOlver for SVM
Proceedings of the 24th international conference on Machine learning
Simpler core vector machines with enclosing balls
Proceedings of the 24th international conference on Machine learning
A dual coordinate descent method for large-scale linear SVM
Proceedings of the 25th international conference on Machine learning
Letters: Adaptive local hyperplane classification
Neurocomputing
Coordinate Descent Method for Large-scale L2-loss Linear Support Vector Machines
The Journal of Machine Learning Research
Exponentiated Gradient Algorithms for Conditional Random Fields and Max-Margin Markov Networks
The Journal of Machine Learning Research
LIBLINEAR: A Library for Large Linear Classification
The Journal of Machine Learning Research
Consistency and Localizability
The Journal of Machine Learning Research
A Scalable Noise Reduction Technique for Large Case-Based Systems
ICCBR '09 Proceedings of the 8th International Conference on Case-Based Reasoning: Case-Based Reasoning Research and Development
Fast Local Support Vector Machines for Large Datasets
MLDM '09 Proceedings of the 6th International Conference on Machine Learning and Data Mining in Pattern Recognition
Sparse kernel SVMs via cutting-plane training
Machine Learning
Cutting-plane training of structural SVMs
Machine Learning
New analysis of the sphere covering problems and optimal polytope approximation of convex bodies
Journal of Approximation Theory
Face recognition with adaptive local hyperplane algorithm
Pattern Analysis & Applications
SGD-QN: Careful Quasi-Newton Stochastic Gradient Descent
The Journal of Machine Learning Research
Noise reduction for instance-based learning with a local maximal margin approach
Journal of Intelligent Information Systems
The huller: a simple and efficient online SVM
ECML'05 Proceedings of the 16th European conference on Machine Learning
A comparison of methods for multiclass support vector machines
IEEE Transactions on Neural Networks
Operators for transforming kernels into quasi-local kernels that improve SVM accuracy
Journal of Intelligent Information Systems
MICCAI'11 Proceedings of the 14th international conference on Medical image computing and computer-assisted intervention - Volume Part III
ICONIP'11 Proceedings of the 18th international conference on Neural Information Processing - Volume Part I
Adaptive weighted fusion of local kernel classifiers for effective pattern classification
ICIC'11 Proceedings of the 7th international conference on Advanced Intelligent Computing
Profiling instances in noise reduction
Knowledge-Based Systems
Parallel and local learning for fast probabilistic neural networks in scalable data mining
Proceedings of the 6th Balkan Conference in Informatics
Universal consistency of localized versions of regularized kernel methods
The Journal of Machine Learning Research
A framework for selection and fusion of pattern classifiers in multimedia recognition
Pattern Recognition Letters
Benchmarking local classification methods
Computational Statistics
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A computationally efficient approach to local learning with kernel methods is presented. The Fast Local Kernel Support Vector Machine (FaLK-SVM) trains a set of local SVMs on redundant neighbourhoods in the training set and an appropriate model for each query point is selected at testing time according to a proximity strategy. Supported by a recent result by Zakai and Ritov (2009) relating consistency and localizability, our approach achieves high classification accuracies by dividing the separation function in local optimisation problems that can be handled very efficiently from the computational viewpoint. The introduction of a fast local model selection further speeds-up the learning process. Learning and complexity bounds are derived for FaLK-SVM, and the empirical evaluation of the approach (with data sets up to 3 million points) showed that it is much faster and more accurate and scalable than state-of-the-art accurate and approximated SVM solvers at least for non high-dimensional data sets. More generally, we show that locality can be an important factor to sensibly speed-up learning approaches and kernel methods, differently from other recent techniques that tend to dismiss local information in order to improve scalability.