The nature of statistical learning theory
The nature of statistical learning theory
Machine Learning
The bias-variance tradeoff and the randomized GACV
Proceedings of the 1998 conference on Advances in neural information processing systems II
Sparse on-line Gaussian processes
Neural Computation
Sparse bayesian learning and the relevance vector machine
The Journal of Machine Learning Research
Healing the relevance vector machine through augmentation
ICML '05 Proceedings of the 22nd international conference on Machine learning
Neural Computation
Assessing Approximate Inference for Binary Gaussian Process Classification
The Journal of Machine Learning Research
Fast Gaussian process methods for point process intensity estimation
Proceedings of the 25th international conference on Machine learning
Sparse multiscale gaussian process regression
Proceedings of the 25th international conference on Machine learning
Learning to rank with SoftRank and Gaussian processes
Proceedings of the 31st annual international ACM SIGIR conference on Research and development in information retrieval
Approximating Gaussian Processes with ${\cal H}^2$-Matrices
ECML '07 Proceedings of the 18th European conference on Machine Learning
Source Separation with Gaussian Process Models
ECML '07 Proceedings of the 18th European conference on Machine Learning
Digital communication receivers using gaussian processes for machine learning
EURASIP Journal on Advances in Signal Processing
Gaussian process dynamic programming
Neurocomputing
An efficient algorithm for learning to rank from preference graphs
Machine Learning
Archipelago: nonparametric Bayesian semi-supervised learning
ICML '09 Proceedings of the 26th Annual International Conference on Machine Learning
Gaussian process regressors for multiuser detection in DS-CDMA systems
IEEE Transactions on Communications
A sparse covariance function for exact Gaussian process inference in large datasets
IJCAI'09 Proceedings of the 21st international jont conference on Artifical intelligence
Anatomically correct testbed hand control: muscle and joint control strategies
ICRA'09 Proceedings of the 2009 IEEE international conference on Robotics and Automation
Extended linear models with Gaussian prior on the parameters and adaptive expansion vectors
ICANN'07 Proceedings of the 17th international conference on Artificial neural networks
Modeling human locomotion with topologically constrained latent variable models
Proceedings of the 2nd conference on Human motion: understanding, modeling, capture and animation
Efficient hold-out for subset of regressors
ICANNGA'09 Proceedings of the 9th international conference on Adaptive and natural computing algorithms
Relevance units latent variable model and nonlinear dimensionality reduction
IEEE Transactions on Neural Networks
Non-parametric Learning to Aid Path Planning over Slopes
International Journal of Robotics Research
Sparse Spectrum Gaussian Process Regression
The Journal of Machine Learning Research
Marginalized neural network mixtures for large-scale regression
IEEE Transactions on Neural Networks
Gaussian process assisted particle swarm optimization
LION'10 Proceedings of the 4th international conference on Learning and intelligent optimization
On Learning and Cross-Validation with Decomposed Nyström Approximation of Kernel Matrix
Neural Processing Letters
Gaussian Processes for Machine Learning (GPML) Toolbox
The Journal of Machine Learning Research
Bayesian Generalized Kernel Mixed Models
The Journal of Machine Learning Research
Physically valid statistical models for human motion generation
ACM Transactions on Graphics (TOG)
Adaptive compression for 3D laser data
International Journal of Robotics Research
Efficient Gaussian process classification using random decision forests
Pattern Recognition and Image Analysis
Computationally Efficient Convolved Multiple Output Gaussian Processes
The Journal of Machine Learning Research
Domain Decomposition Approach for Fast Gaussian Process Regression of Large Spatial Data Sets
The Journal of Machine Learning Research
Sparse Spatio-temporal Gaussian processes with general likelihoods
ICANN'11 Proceedings of the 21th international conference on Artificial neural networks - Volume Part I
On-line regression algorithms for learning mechanical models of robots: A survey
Robotics and Autonomous Systems
Sequential learning with LS-SVM for large-scale data sets
ICANN'06 Proceedings of the 16th international conference on Artificial Neural Networks - Volume Part II
A sparse Gaussian process regression model for tourism demand forecasting in Hong Kong
Expert Systems with Applications: An International Journal
Temporal-Spatial local gaussian process experts for human pose estimation
ACCV'09 Proceedings of the 9th Asian conference on Computer Vision - Volume Part I
Continuous character control with low-dimensional embeddings
ACM Transactions on Graphics (TOG) - SIGGRAPH 2012 Conference Proceedings
Large-scale Gaussian process classification using random decision forests
Pattern Recognition and Image Analysis
Dynamic GP models: an overview and recent developments
ASM'12 Proceedings of the 6th international conference on Applied Mathematics, Simulation, Modelling
Adaptive data compression for robot perception
IJCAI'11 Proceedings of the Twenty-Second international joint conference on Artificial Intelligence - Volume Volume Three
Kernels for Vector-Valued Functions: A Review
Foundations and Trends® in Machine Learning
Efficient space-time modeling for informative sensing
Proceedings of the Sixth International Workshop on Knowledge Discovery from Sensor Data
Motion graphs++: a compact generative model for semantic motion analysis and synthesis
ACM Transactions on Graphics (TOG) - Proceedings of ACM SIGGRAPH Asia 2012
Large-scale gaussian process classification with flexible adaptive histogram kernels
ECCV'12 Proceedings of the 12th European conference on Computer Vision - Volume Part IV
Sparse gaussian processes for multi-task learning
ECML PKDD'12 Proceedings of the 2012 European conference on Machine Learning and Knowledge Discovery in Databases - Volume Part I
Rapid uncertainty computation with gaussian processes and histogram intersection kernels
ACCV'12 Proceedings of the 11th Asian conference on Computer Vision - Volume Part II
Probabilistic movement modeling for intention inference in human-robot interaction
International Journal of Robotics Research
A framework for evaluating approximation methods for Gaussian process regression
The Journal of Machine Learning Research
GPstuff: Bayesian modeling with Gaussian processes
The Journal of Machine Learning Research
Bayesian joint inversions for the exploration of earth resources
IJCAI'13 Proceedings of the Twenty-Third international joint conference on Artificial Intelligence
Gaussian Processes for POMDP-Based Dialogue Manager Optimization
IEEE/ACM Transactions on Audio, Speech and Language Processing (TASLP)
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We provide a new unifying view, including all existing proper probabilistic sparse approximations for Gaussian process regression. Our approach relies on expressing the effective prior which the methods are using. This allows new insights to be gained, and highlights the relationship between existing methods. It also allows for a clear theoretically justified ranking of the closeness of the known approximations to the corresponding full GPs. Finally we point directly to designs of new better sparse approximations, combining the best of the existing strategies, within attractive computational constraints.