A practical Bayesian framework for backpropagation networks
Neural Computation
Some new results on neural network approximation
Neural Networks
Regularization theory and neural networks architectures
Neural Computation
The nature of statistical learning theory
The nature of statistical learning theory
Stochastic processes
Bayesian Learning for Neural Networks
Bayesian Learning for Neural Networks
Evaluation of gaussian processes and other methods for non-linear regression
Evaluation of gaussian processes and other methods for non-linear regression
The generalized Bayesian committee machine
Proceedings of the sixth ACM SIGKDD international conference on Knowledge discovery and data mining
On different facets of regularization theory
Neural Computation
Neural Computation
A graph-based framework for relation propagation and its application to multi-label learning
SIGIR '06 Proceedings of the 29th annual international ACM SIGIR conference on Research and development in information retrieval
Support Vector Machinery for Infinite Ensemble Learning
The Journal of Machine Learning Research
Semi-supervised multi-label learning by constrained non-negative matrix factorization
AAAI'06 Proceedings of the 21st national conference on Artificial intelligence - Volume 1
Features and Metric from a Classifier Improve Visualizations with Dimension Reduction
ICANN '09 Proceedings of the 19th International Conference on Artificial Neural Networks: Part II
Contextual occupancy maps using Gaussian processes
ICRA'09 Proceedings of the 2009 IEEE international conference on Robotics and Automation
Large-margin classification in infinite neural networks
Neural Computation
Recurrent kernel machines: Computing with infinite echo state networks
Neural Computation
Gaussian process occupancy maps*
International Journal of Robotics Research
Transformations of gaussian process priors
Proceedings of the First international conference on Deterministic and Statistical Methods in Machine Learning
Data fusion with Gaussian processes
Robotics and Autonomous Systems
Theoretical analysis of function of derivative term in on-line gradient descent learning
ICANN'12 Proceedings of the 22nd international conference on Artificial Neural Networks and Machine Learning - Volume Part II
Infinite sparse threshold unit networks
ICANN'12 Proceedings of the 22nd international conference on Artificial Neural Networks and Machine Learning - Volume Part I
Semi-parametric learning for visual odometry
International Journal of Robotics Research
Nonparametric guidance of autoencoder representations using label information
The Journal of Machine Learning Research
Hi-index | 0.00 |