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
A Robust Information Clustering Algorithm
Neural Computation
Learning low-rank kernel matrices
ICML '06 Proceedings of the 23rd international conference on Machine learning
Computer Vision and Image Understanding
Gaussian process dynamic programming
Neurocomputing
Maximum likelihood kernel density estimation: On the potential of convolution sieves
Computational Statistics & Data Analysis
Improving effectiveness of mutual information for substantival multiword expression extraction
Expert Systems with Applications: An International Journal
Online prediction of time series data with kernels
IEEE Transactions on Signal Processing
Normalized mutual information feature selection
IEEE Transactions on Neural Networks
Kernel-matching pursuits with arbitrary loss functions
IEEE Transactions on Neural Networks
Information theoretic novelty detection
Pattern Recognition
On the weight convergence of Elman networks
IEEE Transactions on Neural Networks
Using Gaussian process based kernel classifiers for credit rating forecasting
Expert Systems with Applications: An International Journal
Expert Systems with Applications: An International Journal
Expert Systems with Applications: An International Journal
Feature subset selection with cumulate conditional mutual information minimization
Expert Systems with Applications: An International Journal
IEEE Transactions on Signal Processing
The kernel recursive least-squares algorithm
IEEE Transactions on Signal Processing
Fuzzy identification using fuzzy neural networks with stable learning algorithms
IEEE Transactions on Fuzzy Systems
Generalized information potential criterion for adaptive system training
IEEE Transactions on Neural Networks
IEEE Transactions on Neural Networks
An Information Theoretic Approach of Designing Sparse Kernel Adaptive Filters
IEEE Transactions on Neural Networks
Using mutual information for selecting features in supervised neural net learning
IEEE Transactions on Neural Networks
Robust Initialization of a Jordan Network With Recurrent Constrained Learning
IEEE Transactions on Neural Networks - Part 2
Robust Set-Membership Affine-Projection Adaptive-Filtering Algorithm
IEEE Transactions on Signal Processing
A sparse kernel algorithm for online time series data prediction
Expert Systems with Applications: An International Journal
| Hi-index | 12.05 |
Kernel-based algorithms have been proven successful in many nonlinear modeling applications. However, the computational complexity of classical kernel-based methods grows superlinearly with the increasing number of training data, which is too expensive for online applications. In order to solve this problem, the paper presents an information theoretic method to train a sparse version of kernel learning algorithm. A concept named instantaneous mutual information is investigated to measure the system reliability of the estimated output. This measure is used as a criterion to determine the novelty of the training sample and informative ones are selected to form a compact dictionary to represent the whole data. Furthermore, we propose a robust learning scheme for the training of the kernel learning algorithm with an adaptive learning rate. This ensures the convergence of the learning algorithm and makes it converge to the steady state faster. We illustrate the performance of our proposed algorithm and compare it with some recent kernel algorithms by several experiments.