Editorial: Kernel Methods: Current Research and Future Directions
Machine Learning
The Relaxed Online Maximum Margin Algorithm
Machine Learning
Multiclass LS-SVMs: Moderated Outputs and Coding-Decoding Schemes
Neural Processing Letters
Learning curves for Gaussian process regression: approximations and bounds
Neural Computation
Sparse on-line Gaussian processes
Neural Computation
Adapting Kernels by Variational Approach in SVM
AI '02 Proceedings of the 15th Australian Joint Conference on Artificial Intelligence: Advances in Artificial Intelligence
Regularized Principal Manifolds
EuroCOLT '99 Proceedings of the 4th European Conference on Computational Learning Theory
A Generalized Representer Theorem
COLT '01/EuroCOLT '01 Proceedings of the 14th Annual Conference on Computational Learning Theory and and 5th European Conference on Computational Learning Theory
On different facets of regularization theory
Neural Computation
Approximation bounds for some sparse kernel regression algorithms
Neural Computation
Advanced lectures on machine learning
Adaptive Sparseness for Supervised Learning
IEEE Transactions on Pattern Analysis and Machine Intelligence
Regularized principal manifolds
The Journal of Machine Learning Research
Sparse bayesian learning and the relevance vector machine
The Journal of Machine Learning Research
The Journal of Machine Learning Research
Kernel partial least squares regression in reproducing kernel hilbert space
The Journal of Machine Learning Research
Pac-bayesian generalisation error bounds for gaussian process classification
The Journal of Machine Learning Research
The subspace information criterion for infinite dimensional hypothesis spaces
The Journal of Machine Learning Research
The em algorithm for kernel matrix completion with auxiliary data
The Journal of Machine Learning Research
Benchmarking Least Squares Support Vector Machine Classifiers
Machine Learning
A tutorial on support vector regression
Statistics and Computing
Exponential families for conditional random fields
UAI '04 Proceedings of the 20th conference on Uncertainty in artificial intelligence
Hierarchical Gaussian process mixtures for regression
Statistics and Computing
Heteroscedastic Gaussian process regression
ICML '05 Proceedings of the 22nd international conference on Machine learning
Bayesian sparse sampling for on-line reward optimization
ICML '05 Proceedings of the 22nd international conference on Machine learning
Learning Gaussian processes from multiple tasks
ICML '05 Proceedings of the 22nd international conference on Machine learning
Neural Computation
Probabilistic Non-linear Principal Component Analysis with Gaussian Process Latent Variable Models
The Journal of Machine Learning Research
Nonparametric identification of population models via Gaussian processes
Automatica (Journal of IFAC)
Optimising Kernel Parameters and Regularisation Coefficients for Non-linear Discriminant Analysis
The Journal of Machine Learning Research
Second Order Cone Programming Approaches for Handling Missing and Uncertain Data
The Journal of Machine Learning Research
Explicit stochastic predictive control of combustion plants based on Gaussian process models
Automatica (Journal of IFAC)
Digital communication receivers using gaussian processes for machine learning
EURASIP Journal on Advances in Signal Processing
Visual Tracking Using Particle Filters with Gaussian Process Regression
PSIVT '09 Proceedings of the 3rd Pacific Rim Symposium on Advances in Image and Video Technology
Kernel carpentry for online regression using randomly varying coefficient model
IJCAI'07 Proceedings of the 20th international joint conference on Artifical intelligence
Gaussian process models of spatial aggregation algorithms
IJCAI'03 Proceedings of the 18th international joint conference on Artificial intelligence
Gaussian process regressors for multiuser detection in DS-CDMA systems
IEEE Transactions on Communications
EEG signals classification for brain computer interfaces based on Gaussian process classifier
ICICS'09 Proceedings of the 7th international conference on Information, communications and signal processing
Dynamical systems identification using Gaussian process models with incorporated local models
Engineering Applications of Artificial Intelligence
Finite Elements in Analysis and Design
Transductive gaussian process regression with automatic model selection
ECML'06 Proceedings of the 17th European conference on Machine Learning
Computers and Electronics in Agriculture
Sparse gaussian processes using backward elimination
ISNN'06 Proceedings of the Third international conference on Advances in Neural Networks - Volume Part I
Self-tuning control of non-linear systems using gaussian process prior models
Switching and Learning in Feedback Systems
Nonlinear predictive control with a gaussian process model
Switching and Learning in Feedback Systems
Transformations of gaussian process priors
Proceedings of the First international conference on Deterministic and Statistical Methods in Machine Learning
Can gaussian process regression be made robust against model mismatch?
Proceedings of the First international conference on Deterministic and Statistical Methods in Machine Learning
Understanding gaussian process regression using the equivalent kernel
Proceedings of the First international conference on Deterministic and Statistical Methods in Machine Learning
Identification of MIMO Hammerstein models using least squares support vector machines
Automatica (Journal of IFAC)
Inference of disjoint linear and nonlinear sub-domains of a nonlinear mapping
Automatica (Journal of IFAC)
Partially linear support vector machines applied to the prediction of mine slope movements
Mathematical and Computer Modelling: An International Journal
Data fusion with Gaussian processes
Robotics and Autonomous Systems
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