Artificial intelligence: a theoretical approach
Artificial intelligence: a theoretical approach
Structured induction in expert systems
Structured induction in expert systems
Computational limitations on learning from examples
Journal of the ACM (JACM)
Quantitative results concerning the utility of explanation-based learning
Artificial Intelligence
Neural network design and the complexity of learning
Neural network design and the complexity of learning
Boolean Feature Discovery in Empirical Learning
Machine Learning
Training a 3-node neural network in NP-complete
Advances in neural information processing systems 1
Parallel distributed processing: explorations in the microstructure of cognition, vol. 1: foundations
The cascade-correlation learning architecture
Advances in neural information processing systems 2
Advances in neural information processing systems 2
Symbolic-neural systems and the use of hints for developing complex systems
International Journal of Man-Machine Studies
Neural networks: algorithms, applications, and programming techniques
Neural networks: algorithms, applications, and programming techniques
Practical Issues in Temporal Difference Learning
Machine Learning
Constructive higher-order network that is polynomial time
Neural Networks
Neural Computation
A formal model of hierarchical concept learning
Information and Computation
Fundamentals of neural networks: architectures, algorithms, and applications
Fundamentals of neural networks: architectures, algorithms, and applications
Machine Learning - Special issue on inductive transfer
Learning by discovering concept hierarchies
Artificial Intelligence
Artificial Intelligence
A neuroidal architecture for cognitive computation
Journal of the ACM (JACM)
Machine Learning
Learning in Neural Networks: Theoretical Foundations
Learning in Neural Networks: Theoretical Foundations
Visual Development and the Acquisition of Binocular Disparity Sensitivities
ICML '01 Proceedings of the Eighteenth International Conference on Machine Learning
Randomized Variable Elimination
ICML '02 Proceedings of the Nineteenth International Conference on Machine Learning
ICML '00 Proceedings of the Seventeenth International Conference on Machine Learning
Relational Learning for NLP using Linear Threshold Elements
IJCAI '99 Proceedings of the Sixteenth International Joint Conference on Artificial Intelligence
Introduction to the Special Issue on Meta-Learning
Machine Learning
Randomized Variable Elimination
The Journal of Machine Learning Research
Evolving Soccer Keepaway Players Through Task Decomposition
Machine Learning
Tuning evaluation functions by maximizing concordance
Theoretical Computer Science - Advances in computer games
Extracting and composing robust features with denoising autoencoders
Proceedings of the 25th international conference on Machine learning
Learning Representation and Control in Markov Decision Processes: New Frontiers
Foundations and Trends® in Machine Learning
Cross-domain knowledge transfer using structured representations
AAAI'06 Proceedings of the 21st national conference on Artificial intelligence - Volume 1
Samuel meets Amarel: automating value function approximation using global state space analysis
AAAI'05 Proceedings of the 20th national conference on Artificial intelligence - Volume 2
Learning Deep Architectures for AI
Foundations and Trends® in Machine Learning
Constructive neural networks to predict breast cancer outcome by using gene expression profiles
IEA/AIE'10 Proceedings of the 23rd international conference on Industrial engineering and other applications of applied intelligent systems - Volume Part I
The Journal of Machine Learning Research
Studying the hybridization of artificial neural networks in HECIC
IWANN'11 Proceedings of the 11th international conference on Artificial neural networks conference on Advances in computational intelligence - Volume Part II
Structural abstraction experiments in reinforcement learning
AI'05 Proceedings of the 18th Australian Joint conference on Advances in Artificial Intelligence
ML-CIDIM: multiple layers of multiple classifier systems based on CIDIM
RSFDGrC'05 Proceedings of the 10th international conference on Rough Sets, Fuzzy Sets, Data Mining, and Granular Computing - Volume Part II
The learning problem of multi-layer neural networks
Neural Networks
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We explore incremental assimilation of new knowledge by sequential learning. Of particular interest is how a network of many knowledge layers can be constructed in an on-line manner, such that the learned units represent building blocks of knowledge that serve to compress the overall representation and facilitate transfer. We motivate the need for many layers of knowledge, and we advocate sequential learning as an avenue for promoting the construction of layered knowledge structures. Finally, our novel STL algorithm demonstrates a method for simultaneously acquiring and organizing a collection of concepts and functions as a network from a stream of unstructured information.