Theory of linear and integer programming
Theory of linear and integer programming
On the sample complexity of pac-learning using random and chosen examples
COLT '90 Proceedings of the third annual workshop on Computational learning theory
Training connectionist networks with queries and selective sampling
Advances in neural information processing systems 2
Information-based objective functions for active data selection
Neural Computation
Machine Learning
Making large-scale support vector machine learning practical
Advances in kernel methods
Fast training of support vector machines using sequential minimal optimization
Advances in kernel methods
An introduction to support Vector Machines: and other kernel-based learning methods
An introduction to support Vector Machines: and other kernel-based learning methods
Convergence of a Generalized SMO Algorithm for SVM Classifier Design
Machine Learning
The Relaxed Online Maximum Margin Algorithm
Machine Learning
The Kernel-Adatron Algorithm: A Fast and Simple Learning Procedure for Support Vector Machines
ICML '98 Proceedings of the Fifteenth International Conference on Machine Learning
Less is More: Active Learning with Support Vector Machines
ICML '00 Proceedings of the Seventeenth International Conference on Machine Learning
Query Learning with Large Margin Classifiers
ICML '00 Proceedings of the Seventeenth International Conference on Machine Learning
Support Vector Machine Active Learning with Application sto Text Classification
ICML '00 Proceedings of the Seventeenth International Conference on Machine Learning
Automatic Capacity Tuning of Very Large VC-Dimension Classifiers
Advances in Neural Information Processing Systems 5, [NIPS Conference]
MadaBoost: A Modification of AdaBoost
COLT '00 Proceedings of the Thirteenth Annual Conference on Computational Learning Theory
SVMTorch: support vector machines for large-scale regression problems
The Journal of Machine Learning Research
A new approximate maximal margin classification algorithm
The Journal of Machine Learning Research
Ultraconservative online algorithms for multiclass problems
The Journal of Machine Learning Research
On-line learning for very large data sets: Research Articles
Applied Stochastic Models in Business and Industry - Statistical Learning
Estimation of Dependences Based on Empirical Data: Springer Series in Statistics (Springer Series in Statistics)
The huller: a simple and efficient online SVM
ECML'05 Proceedings of the 16th European conference on Machine Learning
On the convergence of the decomposition method for support vector machines
IEEE Transactions on Neural Networks
Fast transpose methods for kernel learning on sparse data
ICML '06 Proceedings of the 23rd international conference on Machine learning
Extraction and search of chemical formulae in text documents on the web
Proceedings of the 16th international conference on World Wide Web
A clustering method for web data with multi-type interrelated components
Proceedings of the 16th international conference on World Wide Web
Step Size Adaptation in Reproducing Kernel Hilbert Space
The Journal of Machine Learning Research
Worst-Case Analysis of Selective Sampling for Linear Classification
The Journal of Machine Learning Research
Maximum-Gain Working Set Selection for SVMs
The Journal of Machine Learning Research
The Journal of Machine Learning Research
Incremental Support Vector Learning: Analysis, Implementation and Applications
The Journal of Machine Learning Research
Solving multiclass support vector machines with LaRank
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
Active learning for class imbalance problem
SIGIR '07 Proceedings of the 30th annual international ACM SIGIR conference on Research and development in information retrieval
Learning on the border: active learning in imbalanced data classification
Proceedings of the sixteenth ACM conference on Conference on information and knowledge management
Second-order smo improves svm online and active learning
Neural Computation
An empirical evaluation of supervised learning in high dimensions
Proceedings of the 25th international conference on Machine learning
Better multiclass classification via a margin-optimized single binary problem
Pattern Recognition Letters
Dynamic Distance-Based Active Learning with SVM
MLDM '07 Proceedings of the 5th international conference on Machine Learning and Data Mining in Pattern Recognition
Sequence Labelling SVMs Trained in One Pass
ECML PKDD '08 Proceedings of the 2008 European Conference on Machine Learning and Knowledge Discovery in Databases - Part I
A Fast Method for Training Linear SVM in the Primal
ECML PKDD '08 Proceedings of the 2008 European Conference on Machine Learning and Knowledge Discovery in Databases - Part I
Incremental Kernel Machines for Protein Remote Homology Detection
HAIS '09 Proceedings of the 4th International Conference on Hybrid Artificial Intelligence Systems
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
Streamed learning: one-pass SVMs
IJCAI'09 Proceedings of the 21st international jont conference on Artifical intelligence
Structured prediction by joint kernel support estimation
Machine Learning
Local properties of RBF-SVM during training for incremental learning
IJCNN'09 Proceedings of the 2009 international joint conference on Neural Networks
On-line independent support vector machines
Pattern Recognition
SGD-QN: Careful Quasi-Newton Stochastic Gradient Descent
The Journal of Machine Learning Research
Support kernel machine-based active learning to find labels and a proper kernel simultaneously
IDEAL'07 Proceedings of the 8th international conference on Intelligent data engineering and automated learning
Consensus-Based Distributed Support Vector Machines
The Journal of Machine Learning Research
Fast and Scalable Local Kernel Machines
The Journal of Machine Learning Research
Example-dependent basis vector selection for kernel-based classifiers
ECML PKDD'10 Proceedings of the 2010 European conference on Machine learning and knowledge discovery in databases: Part III
Condensed vector machines: learning fast machine for large data
IEEE Transactions on Neural Networks
Incremental multiple classifier active learning for concept indexing in images and videos
MMM'11 Proceedings of the 17th international conference on Advances in multimedia modeling - Volume Part I
Tree Decomposition for Large-Scale SVM Problems
The Journal of Machine Learning Research
Identifying, Indexing, and Ranking Chemical Formulae and Chemical Names in Digital Documents
ACM Transactions on Information Systems (TOIS)
Proceedings of the 1st ACM International Conference on Multimedia Retrieval
SALSAS: Sub-linear active learning strategy with approximate k-NN search
Pattern Recognition
Proceedings of the 17th ACM SIGKDD international conference on Knowledge discovery and data mining
Selective block minimization for faster convergence of limited memory large-scale linear models
Proceedings of the 17th ACM SIGKDD international conference on Knowledge discovery and data mining
A GPU-tailored approach for training kernelized SVMs
Proceedings of the 17th ACM SIGKDD international conference on Knowledge discovery and data mining
Double Updating Online Learning
The Journal of Machine Learning Research
Maximum Margin One Class Support Vector Machines for multiclass problems
Pattern Recognition Letters
Efficient supervised optimum-path forest classification for large datasets
Pattern Recognition
Improved working set selection for larank
CAIP'11 Proceedings of the 14th international conference on Computer analysis of images and patterns - Volume Part I
Expert Systems with Applications: An International Journal
Online SVR Training by Solving the Primal Optimization Problem
Journal of Signal Processing Systems
Predicting Metal-Binding Sites from Protein Sequence
IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB)
Efficient name disambiguation for large-scale databases
PKDD'06 Proceedings of the 10th European conference on Principle and Practice of Knowledge Discovery in Databases
Tracking the best hyperplane with a simple budget perceptron
COLT'06 Proceedings of the 19th annual conference on Learning Theory
Active associative sampling for author name disambiguation
Proceedings of the 12th ACM/IEEE-CS joint conference on Digital Libraries
Linear support vector machines via dual cached loops
Proceedings of the 18th ACM SIGKDD international conference on Knowledge discovery and data mining
The bitvector machine: a fast and robust machine learning algorithm for non-linear problems
ECML PKDD'12 Proceedings of the 2012 European conference on Machine Learning and Knowledge Discovery in Databases - Volume Part I
Online learning with multiple kernels: A review
Neural Computation
Learning with infinitely many features
Machine Learning
Large-scale visual concept detection with explicit kernel maps and power mean SVM
Proceedings of the 3rd ACM conference on International conference on multimedia retrieval
A supervised machine learning approach to classify host roles on line using sFlow
Proceedings of the first edition workshop on High performance and programmable networking
Learning non-linear classifiers with a sparsity constraint using L1 regularization
Proceedings of the 28th Annual ACM Symposium on Applied Computing
Structured visual tracking with dynamic graph
ACCV'12 Proceedings of the 11th Asian conference on Computer Vision - Volume Part III
JKernelMachines: a simple framework for kernel machine
The Journal of Machine Learning Research
An introduction to artificial prediction markets for classification
The Journal of Machine Learning Research
The Journal of Machine Learning Research
Co-trained generative and discriminative trackers with cascade particle filter
Computer Vision and Image Understanding
Online learning algorithm of kernel-based ternary classifiers using support vectors
Optical Memory and Neural Networks
Imbalanced evolving self-organizing learning
Neurocomputing
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Very high dimensional learning systems become theoretically possible when training examples are abundant. The computing cost then becomes the limiting factor. Any efficient learning algorithm should at least take a brief look at each example. But should all examples be given equal attention?This contribution proposes an empirical answer. We first present an online SVM algorithm based on this premise. LASVM yields competitive misclassification rates after a single pass over the training examples, outspeeding state-of-the-art SVM solvers. Then we show how active example selection can yield faster training, higher accuracies, and simpler models, using only a fraction of the training example labels.