Communications of the ACM
A massively parallel architecture for a self-organizing neural pattern recognition machine
Computer Vision, Graphics, and Image Processing
Fuzzy sets, uncertainty, and information
Fuzzy sets, uncertainty, and information
Shafer-dempster reasoning with applications to multisensor target identification systems
IEEE Transactions on Systems, Man and Cybernetics
Learnability and the Vapnik-Chervonenkis dimension
Journal of the ACM (JACM)
The Combination of Evidence in the Transferable Belief Model
IEEE Transactions on Pattern Analysis and Machine Intelligence
Learning and applying contextual constraints in sentence comprehension
Artificial Intelligence - On connectionist symbol processing
Adaptive resonance theory with supervised learning and large database applications
Adaptive resonance theory with supervised learning and large database applications
An introduction to computational learning theory
An introduction to computational learning theory
Fuzzy adaptive learning control network with on-line neural learning
Fuzzy Sets and Systems - Special issue on fuzzy control
Adaptive resonance associative map
Neural Networks
Fuzzy set theory—and its applications (3rd ed.)
Fuzzy set theory—and its applications (3rd ed.)
Self-organizing maps
Support Vector Machines for 3D Object Recognition
IEEE Transactions on Pattern Analysis and Machine Intelligence
Decision Rule for Pattern Classification by Integrating Interval Feature Values
IEEE Transactions on Pattern Analysis and Machine Intelligence
Competitive Learning Algorithms and Neurocomputer Architecture
IEEE Transactions on Computers
Integrating Faces and Fingerprints for Personal Identification
IEEE Transactions on Pattern Analysis and Machine Intelligence
Properties of learning of a fuzzy ART variant
Neural Networks
A Theory of Learning and Generalization: With Applications to Neural Networks and Control Systems
A Theory of Learning and Generalization: With Applications to Neural Networks and Control Systems
Computational Intelligence: Imitating Life
Computational Intelligence: Imitating Life
Expert Systems: Principles and Programming
Expert Systems: Principles and Programming
Using a Hash-Based Method with Transaction Trimming for Mining Association Rules
IEEE Transactions on Knowledge and Data Engineering
A Qualitative Discriminant Approach for Generating Quantitative Belief Functions
IEEE Transactions on Knowledge and Data Engineering
Compile-Time and Runtime Analysis of Active Behaviors
IEEE Transactions on Knowledge and Data Engineering
A Framework for Learning in Search-Based Systems
IEEE Transactions on Knowledge and Data Engineering
Rule-Induction and Case-Based Reasoning: Hybrid Architectures Appear Advantageous
IEEE Transactions on Knowledge and Data Engineering
Overcoming Process Delays with Decision Tree Induction
IEEE Expert: Intelligent Systems and Their Applications
Nonlinear system modeling by competitive learning and adaptivefuzzy inference system
IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews
An evidence-theoretic k-NN rule with parameter optimization
IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews
Global stability of generalized additive fuzzy systems
IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews
A parallel fuzzy inference model with distributed prediction schemefor reinforcement learning
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Similarity measures in fuzzy rule base simplification
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
A statistical approach to the representation of uncertainty in beliefs using spread of opinions
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
Transferable belief model for decision making in the valuation-based systems
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
On the aggregation of prioritized belief structures
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
The modified Dempster-Shafer approach to classification
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
A target identification comparison of Bayesian and Dempster-Shafer multisensor fusion
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
Fuzzy bounded least-squares method for the identification of linear systems
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
Fuzzy logic = computing with words
IEEE Transactions on Fuzzy Systems
Generalization of the Dempster-Shafer theory: a fuzzy-valued measure
IEEE Transactions on Fuzzy Systems
A theory of independent fuzzy probability for system reliability
IEEE Transactions on Fuzzy Systems
Learning in the framework of fuzzy lattices
IEEE Transactions on Fuzzy Systems
On neurobiological, neuro-fuzzy, machine learning, and statistical pattern recognition techniques
IEEE Transactions on Neural Networks
Acquiring rule sets as a product of learning in a logical neural architecture
IEEE Transactions on Neural Networks
Fuzzy lattice neural network (FLNN): a hybrid model for learning
IEEE Transactions on Neural Networks
Learning without local minima in radial basis function networks
IEEE Transactions on Neural Networks
The Journal of Machine Learning Research
Fuzzy lattice reasoning (FLR) classifier and its application for ambient ozone estimation
International Journal of Approximate Reasoning
Partial and Fuzzy Constraint Satisfaction to Support Coalition Formation
Electronic Notes in Theoretical Computer Science (ENTCS)
Effective Learning with Heterogeneous Neural Networks
Neural Information Processing
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A novel theoretical framework is delineated for supervised and unsupervised learning. It is called framework of fuzzy lattices, or FL-framework for short, and it suggests mathematically sound tools for dealing separately and/or jointly with disparate types of data including vectors of numbers, fuzzy sets, symbols, etc. Specific schemes are proposed for clustering and classification having the capacity to deal with both missing and don't care data values; the schemes in question can be implemented as neural networks. The proposed learning schemes are employed here for pattern recognition on seven data sets including benchmark data sets, and the results are compared with those ones by various learning techniques from the literature. Finally, aiming at a mutual cross-fertilization, the FL-framework is associated with established theories for learning and/or decision-making including probability theory, fuzzy set theory, Bayesian decision-making, theory of evidence, and adaptive resonance theory.