The nature of statistical learning theory
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Fast training of support vector machines using sequential minimal optimization
Advances in kernel methods
Handling concept drifts in incremental learning with support vector machines
KDD '99 Proceedings of the fifth ACM SIGKDD international conference on Knowledge discovery and data mining
An introduction to support Vector Machines: and other kernel-based learning methods
An introduction to support Vector Machines: and other kernel-based learning methods
AI Game Programming Wisdom
Choosing Multiple Parameters for Support Vector Machines
Machine Learning
Incremental Support Vector Machine Learning: A Local Approach
ICANN '01 Proceedings of the International Conference on Artificial Neural Networks
SVMTorch: support vector machines for large-scale regression problems
The Journal of Machine Learning Research
Exact simplification of support vector solutions
The Journal of Machine Learning Research
Support vector regression for classifier prediction
Proceedings of the 9th annual conference on Genetic and evolutionary computation
The projectron: a bounded kernel-based Perceptron
Proceedings of the 25th international conference on Machine learning
Support vector machines regression and modeling of greenhouse environment
Computers and Electronics in Agriculture
Kernelized value function approximation for reinforcement learning
ICML '09 Proceedings of the 26th Annual International Conference on Machine Learning
Extended kernel recursive least squares algorithm
IEEE Transactions on Signal Processing
Online modeling based on support vector machine
CCDC'09 Proceedings of the 21st annual international conference on Chinese Control and Decision Conference
Sparse online model learning for robot control with support vector regression
IROS'09 Proceedings of the 2009 IEEE/RSJ international conference on Intelligent robots and systems
Smooth Bayesian kernel machines
ICANN'05 Proceedings of the 15th international conference on Artificial neural networks: formal models and their applications - Volume Part II
Sparse Kernel-SARSA(λ) with an eligibility trace
ECML PKDD'11 Proceedings of the 2011 European conference on Machine learning and knowledge discovery in databases - Volume Part III
A kernel-based Perceptron with dynamic memory
Neural Networks
Concept updating with support vector machines
WAIM'05 Proceedings of the 6th international conference on Advances in Web-Age Information Management
Learning interpretable SVMs for biological sequence classification
RECOMB'05 Proceedings of the 9th Annual international conference on Research in Computational Molecular Biology
IWANN'05 Proceedings of the 8th international conference on Artificial Neural Networks: computational Intelligence and Bioinspired Systems
The Journal of Machine Learning Research
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We present a novel algorithm for sparse online greedy kernel-based nonlinear regression. This algorithm improves current approaches to kernel-based regression in two aspects. First, it operates online - at each time step it observes a single new input sample, performs an update and discards it. Second, the solution maintained is extremely sparse. This is achieved by an explicit greedy sparsification process that admits into the kernel representation a new input sample only if its feature space image is linearly independent of the images of previously admitted samples. We show that the algorithm implements a form of gradient ascent and demonstrate its scaling and noise tolerance properties on three benchmark regression problems.