Kernel Predictive Linear Gaussian models for nonlinear stochastic dynamical systems
ICML '06 Proceedings of the 23rd international conference on Machine learning
Sequential Bayesian kernel modelling with non-Gaussian noise
Neural Networks
Machine learning approaches to network anomaly detection
SYSML'07 Proceedings of the 2nd USENIX workshop on Tackling computer systems problems with machine learning techniques
EURASIP Journal on Advances in Signal Processing
A Kernel-Based Reinforcement Learning Approach to Dynamic Behavior Modeling of Intrusion Detection
ISNN '07 Proceedings of the 4th international symposium on Neural Networks: Advances in Neural Networks
Machinery Fault Diagnosis Using Least Squares Support Vector Machine
ISNN '07 Proceedings of the 4th international symposium on Neural Networks: Advances in Neural Networks, Part III
Model selection approaches for non-linear system identification: a review
International Journal of Systems Science
Kernel least mean square algorithm with constrained growth
Signal Processing
Regularized Fitted Q-Iteration: Application to Planning
Recent Advances in Reinforcement Learning
Reordering Sparsification of Kernel Machines in Approximate Policy Iteration
ISNN 2009 Proceedings of the 6th International Symposium on Neural Networks: Advances in Neural Networks - Part II
Reinforcement Learning Control of a Real Mobile Robot Using Approximate Policy Iteration
ISNN 2009 Proceedings of the 6th International Symposium on Neural Networks: Advances in Neural Networks - Part III
Least Squares SVM for Least Squares TD Learning
Proceedings of the 2006 conference on ECAI 2006: 17th European Conference on Artificial Intelligence August 29 -- September 1, 2006, Riva del Garda, Italy
Mixtures of predictive linear Gaussian models for nonlinear stochastic dynamical systems
AAAI'06 Proceedings of the 21st national conference on Artificial intelligence - Volume 1
Online prediction of time series data with kernels
IEEE Transactions on Signal Processing
Extended kernel recursive least squares algorithm
IEEE Transactions on Signal Processing
Model-based and model-free reinforcement learning for visual servoing
ICRA'09 Proceedings of the 2009 IEEE international conference on Robotics and Automation
On-line independent support vector machines
Pattern Recognition
Adaptive constrained learning in reproducing Kernel Hilbert spaces: the robust beamforming case
IEEE Transactions on Signal Processing
Blind MIMO-OFDM channel estimation based on ICA and KRLS algorithm
WiCOM'09 Proceedings of the 5th International Conference on Wireless communications, networking and mobile computing
Dlib-ml: A Machine Learning Toolkit
The Journal of Machine Learning Research
Bounded Kernel-Based Online Learning
The Journal of Machine Learning Research
MRA Kernel matching pursuit machine
PRICAI'06 Proceedings of the 9th Pacific Rim international conference on Artificial intelligence
Sparse kernel-based feature weighting
PAKDD'08 Proceedings of the 12th Pacific-Asia conference on Advances in knowledge discovery and data mining
An improved distinguishing different vowel sounds of language approach
FSKD'09 Proceedings of the 6th international conference on Fuzzy systems and knowledge discovery - Volume 1
Online anomaly detection using KDE
GLOBECOM'09 Proceedings of the 28th IEEE conference on Global telecommunications
An effective method of pruning support vector machine classifiers
IEEE Transactions on Neural Networks
Sparse approximation through boosting for learning large scale kernel machines
IEEE Transactions on Neural Networks
Adaptive kernel-based image denoising employing semi-parametric regularization
IEEE Transactions on Image Processing
The complex Gaussian kernel LMS algorithm
ICANN'10 Proceedings of the 20th international conference on Artificial neural networks: Part II
Error tolerance based support vector machine for regression
Neurocomputing
A decentralized approach for nonlinear prediction of time series data in sensor networks
EURASIP Journal on Wireless Communications and Networking - Special issue on theoretical and algorithmic foundations of wireless ad hoc and sensor networks
Sparse approximate dynamic programming for dialog management
SIGDIAL '10 Proceedings of the 11th Annual Meeting of the Special Interest Group on Discourse and Dialogue
Sample-efficient batch reinforcement learning for dialogue management optimization
ACM Transactions on Speech and Language Processing (TSLP)
Regression models for texture image analysis
PReMI'11 Proceedings of the 4th international conference on Pattern recognition and machine intelligence
On-line regression algorithms for learning mechanical models of robots: A survey
Robotics and Autonomous Systems
Area-to-point kernel regression on streaming data
Proceedings of the 2nd ACM SIGSPATIAL International Workshop on GeoStreaming
A kernel-based Perceptron with dynamic memory
Neural Networks
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 kernel-based least-squares temporal difference algorithm for reinforcement learning
ICNC'06 Proceedings of the Second international conference on Advances in Natural Computation - Volume Part I
Kernel matching pursuit based on immune clonal algorithm for image recognition
SEAL'06 Proceedings of the 6th international conference on Simulated Evolution And Learning
Base vector selection for kernel matching pursuit
ADMA'06 Proceedings of the Second international conference on Advanced Data Mining and Applications
An online AUC formulation for binary classification
Pattern Recognition
IWANN'05 Proceedings of the 8th international conference on Artificial Neural Networks: computational Intelligence and Bioinspired Systems
Computational advantages of reverberating loops for sensorimotor learning
Neural Computation
Wavelet kernel matching pursuit machine
AI'06 Proceedings of the 19th Australian joint conference on Artificial Intelligence: advances in Artificial Intelligence
Adaptive optimal control without weight transport
Neural Computation
Pruning least objective contribution in KMSE
Neurocomputing
Mean square convergence analysis for kernel least mean square algorithm
Signal Processing
IScIDE'11 Proceedings of the Second Sino-foreign-interchange conference on Intelligent Science and Intelligent Data Engineering
A rapid sparsification method for kernel machines in approximate policy iteration
ISNN'12 Proceedings of the 9th international conference on Advances in Neural Networks - Volume Part I
Dictionary construction for patch-to-tensor embedding
IDA'12 Proceedings of the 11th international conference on Advances in Intelligent Data Analysis
A sparse kernel algorithm for online time series data prediction
Expert Systems with Applications: An International Journal
Kernel-Tree: mining frequent patterns in a data stream based on forecast support
AI'12 Proceedings of the 25th Australasian joint conference on Advances in Artificial Intelligence
Fixed budget quantized kernel least-mean-square algorithm
Signal Processing
Kernel minimum error entropy algorithm
Neurocomputing
An information theoretic sparse kernel algorithm for online learning
Expert Systems with Applications: An International Journal
| Hi-index | 35.70 |
We present a nonlinear version of the recursive least squares (RLS) algorithm. Our algorithm performs linear regression in a high-dimensional feature space induced by a Mercer kernel and can therefore be used to recursively construct minimum mean-squared-error solutions to nonlinear least-squares problems that are frequently encountered in signal processing applications. In order to regularize solutions and keep the complexity of the algorithm bounded, we use a sequential sparsification process that admits into the kernel representation a new input sample only if its feature space image cannot be sufficiently well approximated by combining the images of previously admitted samples. This sparsification procedure allows the algorithm to operate online, often in real time. We analyze the behavior of the algorithm, compare its scaling properties to those of support vector machines, and demonstrate its utility in solving two signal processing problems-time-series prediction and channel equalization.