Journal of Computer and System Sciences
The nature of statistical learning theory
The nature of statistical learning theory
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
A game of prediction with expert advice
Journal of Computer and System Sciences - Special issue on the eighth annual workshop on computational learning theory, July 5–8, 1995
Machine Learning - Special issue on context sensitivity and concept drift
Large Margin Classification Using the Perceptron Algorithm
Machine Learning - The Eleventh Annual Conference on computational Learning Theory
Mean field methods for classification with Gaussian processes
Proceedings of the 1998 conference on Advances in neural information processing systems II
Machine Learning
Linear Programming Boosting via Column Generation
Machine Learning
Multiresolution Gray-Scale and Rotation Invariant Texture Classification with Local Binary Patterns
IEEE Transactions on Pattern Analysis and Machine Intelligence
Sparse on-line Gaussian processes
Neural Computation
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
Large Margin Classification for Moving Targets
ALT '02 Proceedings of the 13th International Conference on Algorithmic Learning Theory
Learning Additive Models Online with Fast Evaluating Kernels
COLT '01/EuroCOLT '01 Proceedings of the 14th Annual Conference on Computational Learning Theory and and 5th European Conference on Computational Learning Theory
Object Recognition from Local Scale-Invariant Features
ICCV '99 Proceedings of the International Conference on Computer Vision-Volume 2 - Volume 2
Tracking the best linear predictor
The Journal of Machine Learning Research
Support vector machine active learning with applications to text classification
The Journal of Machine Learning Research
Kernel Methods for Pattern Analysis
Kernel Methods for Pattern Analysis
Learning the Kernel Matrix with Semidefinite Programming
The Journal of Machine Learning Research
Solving large scale linear prediction problems using stochastic gradient descent algorithms
ICML '04 Proceedings of the twenty-first international conference on Machine learning
Links between perceptrons, MLPs and SVMs
ICML '04 Proceedings of the twenty-first international conference on Machine learning
Multiple kernel learning, conic duality, and the SMO algorithm
ICML '04 Proceedings of the twenty-first international conference on Machine learning
CVPRW '04 Proceedings of the 2004 Conference on Computer Vision and Pattern Recognition Workshop (CVPRW'04) Volume 12 - Volume 12
Reinforcement learning with Gaussian processes
ICML '05 Proceedings of the 22nd international conference on Machine learning
Hierarchic Bayesian models for kernel learning
ICML '05 Proceedings of the 22nd international conference on Machine learning
ICML '05 Proceedings of the 22nd international conference on Machine learning
One-Shot Learning of Object Categories
IEEE Transactions on Pattern Analysis and Machine Intelligence
Online multiclass learning by interclass hypothesis sharing
ICML '06 Proceedings of the 23rd international conference on Machine learning
Gaussian Processes for Machine Learning (Adaptive Computation and Machine Learning)
Gaussian Processes for Machine Learning (Adaptive Computation and Machine Learning)
Ensemble classifier for protein fold pattern recognition
Bioinformatics
Fast Kernel Classifiers with Online and Active Learning
The Journal of Machine Learning Research
Assessing Approximate Inference for Binary Gaussian Process Classification
The Journal of Machine Learning Research
Online Passive-Aggressive Algorithms
The Journal of Machine Learning Research
Learning nonparametric kernel matrices from pairwise constraints
Proceedings of the 24th international conference on Machine learning
Multiclass multiple kernel learning
Proceedings of the 24th international conference on Machine learning
Representing shape with a spatial pyramid kernel
Proceedings of the 6th ACM international conference on Image and video retrieval
Tracking the best hyperplane with a simple budget Perceptron
Machine Learning
A primal-dual perspective of online learning algorithms
Machine Learning
The Forgetron: A Kernel-Based Perceptron on a Budget
SIAM Journal on Computing
Probabilistic multi-class multi-kernel learning
Bioinformatics
Online kernel selection for Bayesian reinforcement learning
Proceedings of the 25th international conference on Machine learning
Consistency of the Group Lasso and Multiple Kernel Learning
The Journal of Machine Learning Research
Hoeffding and Bernstein races for selecting policies in evolutionary direct policy search
ICML '09 Proceedings of the 26th Annual International Conference on Machine Learning
A simpler unified analysis of budget perceptrons
ICML '09 Proceedings of the 26th Annual International Conference on Machine Learning
SimpleNPKL: simple non-parametric kernel learning
ICML '09 Proceedings of the 26th Annual International Conference on Machine Learning
Combining feature spaces for classification
Pattern Recognition
Robust Stochastic Approximation Approach to Stochastic Programming
SIAM Journal on Optimization
On-line independent support vector machines
Pattern Recognition
Bounded Kernel-Based Online Learning
The Journal of Machine Learning Research
Virtual vector machine for Bayesian online classification
UAI '09 Proceedings of the Twenty-Fifth Conference on Uncertainty in Artificial Intelligence
Online multiple kernel learning: algorithms and mistake bounds
ALT'10 Proceedings of the 21st international conference on Algorithmic learning theory
lp-Norm Multiple Kernel Learning
The Journal of Machine Learning Research
Adaptive Subgradient Methods for Online Learning and Stochastic Optimization
The Journal of Machine Learning Research
Multiple Kernel Learning Algorithms
The Journal of Machine Learning Research
On the generalization ability of on-line learning algorithms
IEEE Transactions on Information Theory
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This review examines kernel methods for online learning, in particular, multiclass classification. We examine margin-based approaches, stemming from Rosenblatt's original perceptron algorithm, as well as nonparametric probabilistic approaches that are based on the popular gaussian process framework. We also examine approaches to online learning that use combinations of kernels-online multiple kernel learning. We present empirical validation of a wide range of methods on a protein fold recognition data set, where different biological feature types are available, and two object recognition data sets, Caltech101 and Caltech256, where multiple feature spaces are available in terms of different image feature extraction methods.