Learning internal representations by error propagation
Parallel distributed processing: explorations in the microstructure of cognition, vol. 1
Note on learning rate schedules for stochastic optimization
NIPS-3 Proceedings of the 1990 conference on Advances in neural information processing systems 3
Independent component analysis, a new concept?
Signal Processing - Special issue on higher order statistics
Natural gradient works efficiently in learning
Neural Computation
Online learning from finite training sets in nonlinear networks
NIPS '97 Proceedings of the 1997 conference on Advances in neural information processing systems 10
Unsupervised on-line learning of decision trees for hierarchical data analysis
NIPS '97 Proceedings of the 1997 conference on Advances in neural information processing systems 10
On-line learning in neural networks
On-line learning in neural networks
A statistical study of on-line learning
On-line learning in neural networks
On-line learning in switching and drifting environments with application to blind source separation
On-line learning in neural networks
Parameter adaptation in stochastic optimization
On-line learning in neural networks
Neural Networks for Pattern Recognition
Neural Networks for Pattern Recognition
An Information-Theoretic Approach to Neural Computing
An Information-Theoretic Approach to Neural Computing
Fast curvature matrix-vector products for second-order gradient descent
Neural Computation
Local Gain Adaptation in Stochastic Gradient Descent
Local Gain Adaptation in Stochastic Gradient Descent
Backpropagation applied to handwritten zip code recognition
Neural Computation
Equivariant adaptive source separation
IEEE Transactions on Signal Processing
Metalearning and neuromodulation
Neural Networks - Computational models of neuromodulation
Blind source separation of more sources than mixtures using sparse mixture models
Pattern Recognition Letters
A SOM-based data mining strategy for adaptive modelling of an offset lithographic printing process
Engineering Applications of Artificial Intelligence
Incremental Support Vector Learning: Analysis, Implementation and Applications
The Journal of Machine Learning Research
EURASIP Journal on Applied Signal Processing
Covariate Shift Adaptation by Importance Weighted Cross Validation
The Journal of Machine Learning Research
ICA '09 Proceedings of the 8th International Conference on Independent Component Analysis and Signal Separation
Tracking a moving hypothesis for visual data with explicit switch detection
CISDA'09 Proceedings of the Second IEEE international conference on Computational intelligence for security and defense applications
Inference from aging information
IEEE Transactions on Neural Networks
Asilomar'09 Proceedings of the 43rd Asilomar conference on Signals, systems and computers
Information Sciences: an International Journal
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An adaptive on-line algorithm extending the learning of learning idea is proposed and theoretically motivated. Relying only on gradient flow information it can be applied to learning continuous functions or distributions, even when no explicit loss function is given and the Hessian is not available. The framework is applied for unsupervised and supervised learning. Its efficiency is demonstrated for drifting and switching non-stationary blind separation tasks of acoustic signals. Furthermore applications to classification (US postal service data set) and time-series prediction in changing environments are presented.