Adaptive signal processing
Self-organization and associative memory: 3rd edition
Self-organization and associative memory: 3rd edition
Information controller to maximize and minimize information
Neural Computation
A learning theorem for networks at detailed stochastic equilibrium
Neural Computation
A Review of Statistical Language Processing Techniques
Artificial Intelligence Review
Fast temporal encoding and decoding with spiking neurons
Neural Computation
Mutual information, Fisher information, and population coding
Neural Computation
Feature extraction through LOCOCODE
Neural Computation
Evolutionary Pursuit and Its Application to Face Recognition
IEEE Transactions on Pattern Analysis and Machine Intelligence
Measures for the organization of self-organizing maps
Self-Organizing neural networks
Neural networks with local receptive fields and superlinear VC Dimension
Neural Computation
Towards a New Information Processing Measure for Neural Computation
ICANN '02 Proceedings of the International Conference on Artificial Neural Networks
Information Maximization and Language Acquisition
ICANN '01 Proceedings of the International Conference on Artificial Neural Networks
Locality of global stochastic interaction in directed acyclic networks
Neural Computation
Probabilistic Reasoning Models for Face Recognition
CVPR '98 Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition
Self-organized learning in multi-layer networks
INBS '95 Proceedings of the First International Symposium on Intelligence in Neural and Biological Systems (INBS'95)
Stochastic resonance in noisy threshold neurons
Neural Networks - 2003 Special issue: Advances in neural networks research — IJCNN'03
Information-Theoretic Competitive Learning with Inverse Euclidean Distance Output Units
Neural Processing Letters
Dynamical properties of strongly interacting Markov chains
Neural Networks
Multi-Channel Subspace Mapping Using an Information Maximization Criterion
Multidimensional Systems and Signal Processing
Modeling cognitive processes in information seeking: from popper to pask
Journal of the American Society for Information Science and Technology - Special issue: Part II: Information seeking research
Information Bottleneck for Gaussian Variables
The Journal of Machine Learning Research
Active Vision and Receptive Field Development in Evolutionary Robots
Evolutionary Computation
A Complex Cell–Like Receptive Field Obtained by Information Maximization
Neural Computation
2005 Special Issue: Unifying cost and information in information-theoretic competitive learning
Neural Networks - 2005 Special issue: IJCNN 2005
A Statistical Theory of Long-Term Potentiation and Depression
Neural Computation
Learning Overcomplete Representations
Neural Computation
Images, Frames, and Connectionist Hierarchies
Neural Computation
The Journal of Machine Learning Research
Neural network explanation using inversion
Neural Networks
Learning sensory representations with intrinsic plasticity
Neurocomputing
EXPLOITING THE CONSTRUCTION OF E-LEARNER COMMUNITIES FROM A TRUST CONNECTIONIST POINT OF VIEW
Journal of Integrated Design & Process Science
Computers in Biology and Medicine
Factor Analysis Using Delta-Rule Wake-Sleep Learning
Neural Computation
Error Entropy in Classification Problems: A Univariate Data Analysis
Neural Computation
Information maximization in face processing
Neurocomputing
Cognitive vision: The case for embodied perception
Image and Vision Computing
Using learning to facilitate the evolution of features for recognizing visual concepts
Evolutionary Computation
Towards a theory of early visual processing
Neural Computation
Neural Computation
Informax principle-based query expansion using Hopfield neural networks
International Journal of Intelligent Systems Technologies and Applications
On neurodynamics with limiter function and linsker's developmental model
Neural Computation
Semilinear predictability minimization produces well-known feature detectors
Neural Computation
Reduced representation by neural networks with restricted receptive fields
Neural Computation
Neural Computation
An Overcomplete ICA Algorithm by InfoMax and InfoMin
ICANN '08 Proceedings of the 18th international conference on Artificial Neural Networks, Part I
Feature Discovery by Enhancement and Relaxation of Competitive Units
IDEAL '08 Proceedings of the 9th International Conference on Intelligent Data Engineering and Automated Learning
The radar-graphic speech learning system for hearing impaired
Expert Systems with Applications: An International Journal
A refinement of the common cause principle
Discrete Applied Mathematics
Enhancing and Relaxing Competitive Units for Feature Discovery
Neural Processing Letters
Hybrid learning using genetic algorithms and decision trees for pattern classification
IJCAI'95 Proceedings of the 14th international joint conference on Artificial intelligence - Volume 1
Info-margin maximization for feature extraction
Pattern Recognition Letters
Self-enhancement learning: self-supervised and target-creating learning
IJCNN'09 Proceedings of the 2009 international joint conference on Neural Networks
A computational platform for visual fear conditioning
IJCNN'09 Proceedings of the 2009 international joint conference on Neural Networks
Structural enhanced information to detect features in competitive learning
SMC'09 Proceedings of the 2009 IEEE international conference on Systems, Man and Cybernetics
SMC'09 Proceedings of the 2009 IEEE international conference on Systems, Man and Cybernetics
International Journal of Artificial Intelligence and Soft Computing
Competitive learning by information maximization: eliminating dead neurons in competitive learning
ICANN/ICONIP'03 Proceedings of the 2003 joint international conference on Artificial neural networks and neural information processing
The infomin criterion: an information theoretic unifying objective function for topographic mappings
ICANN/ICONIP'03 Proceedings of the 2003 joint international conference on Artificial neural networks and neural information processing
How information and embodiment shape intelligent information processing
50 years of artificial intelligence
Capacity analysis for integrate-and-fire neurons with descending action potential thresholds
IEEE Transactions on Information Theory - Special issue on information theory in molecular biology and neuroscience
Higher Coordination With Less Control-A Result of Information Maximization in the Sensorimotor Loop
Adaptive Behavior - Animals, Animats, Software Agents, Robots, Adaptive Systems
The mee principle in data classification: A perceptron-based analysis
Neural Computation
Artificial Life
Generation of comprehensible representations by supposed maximum information
ICANN'10 Proceedings of the 20th international conference on Artificial neural networks: Part II
Scalable discriminant feature selection for image retrieval and recognition
CVPR'04 Proceedings of the 2004 IEEE computer society conference on Computer vision and pattern recognition
Domain of attraction on adaptive feature extraction of nonstationary processes
ICASSP'93 Proceedings of the 1993 IEEE international conference on Acoustics, speech, and signal processing: plenary, special, audio, underwater acoustics, VLSI, neural networks - Volume I
Feature selection by maximum marginal diversity: optimality and implications for visual recognition
CVPR'03 Proceedings of the 2003 IEEE computer society conference on Computer vision and pattern recognition
Maximizing the ratio of information to its cost in information theoretic competitive learning
ICANN'05 Proceedings of the 15th international conference on Artificial neural networks: formal models and their applications - Volume Part II
Design of a smart biomarker for bioremediation: A machine learning approach
Computers in Biology and Medicine
Attractor memory with self-organizing input
BioADIT'06 Proceedings of the Second international conference on Biologically Inspired Approaches to Advanced Information Technology
ICONIP'06 Proceedings of the 13 international conference on Neural Information Processing - Volume Part I
Object recognition using a neural network with optimal feature extraction
Mathematical and Computer Modelling: An International Journal
Modeling learned categorical perception in human vision
Neural Networks
| Hi-index | 4.10 |
The emergence of a feature-analyzing function from the development rules of simple, multilayered networks is explored. It is shown that even a single developing cell of a layered network exhibits a remarkable set of optimization properties that are closely related to issues in statistics, theoretical physics, adaptive signal processing, the formation of knowledge representation in artificial intelligence, and information theory. The network studied is based on the visual system. These results are used to infer an information-theoretic principle that can be applied to the network as a whole, rather than a single cell. The organizing principle proposed is that the network connections develop in such a way as to maximize the amount of information that is preserved when signals are transformed at each processing stage, subject to certain constraints. The operation of this principle is illustrated for some simple cases.