On the Need for a Neural Abstract Machine

Neural network design and the complexity of learning

Neural network design and the complexity of learning

Learning from hints in neural networks

Journal of Complexity

Parallel distributed processing: explorations in the microstructure of cognition, vol. 1: foundations

Parallel distributed processing: explorations in the microstructure of cognition, vol. 1: foundations

The recurrent cascade-correlation architecture

NIPS-3 Proceedings of the 1990 conference on Advances in neural information processing systems 3

Practical Issues in Temporal Difference Learning

Machine Learning

Neural networks and the bias/variance dilemma

Neural Computation

First- and second-order methods for learning: between steepest descent and Newton's method

Neural Computation

Learning complex, extended sequences using the principle of history compression

Neural Computation

Learning and extracting finite state automata with second-order recurrent neural networks

Neural Computation

Neural networks and nonlinear adaptive filtering: unifying concepts and new algorithms

Neural Computation

Hints and the VC dimension

Neural Computation

Extracting Refined Rules from Knowledge-Based Neural Networks

Machine Learning

Refining algorithms with knowledge-based neural networks: improving the Chou-Fasman algorithm for protein folding

Proceedings of a workshop on Computational learning theory and natural learning systems (vol. 1) : constraints and prospects: constraints and prospects

Block-structured recurrent neural networks

Neural Networks

Hints

Neural Computation

On the computational power of neural nets

Journal of Computer and System Sciences

Learning the initial state of a second-order recurrent neural network during regular-language inference

Neural Computation

An algebraic framework to represent finite state machines in single-layer recurrent neural networks

Neural Computation

Evolving algebras 1993: Lipari guide

Specification and validation methods

Constructing deterministic finite-state automata in recurrent neural networks

Journal of the ACM (JACM)

Information geometry of the EM and em algorithms for neural networks

Neural Networks

Learning to Predict by the Methods of Temporal Differences

Machine Learning

A Method for Learning From Hints

Advances in Neural Information Processing Systems 5, [NIPS Conference]

Integration of Graphical Rules with Adaptive Learning of Structured Information

Hybrid Neural Systems, revised papers from a workshop

Why Use Evolving Algebras for Hardware and Software Engineering?

SOFSEM '95 Proceedings of the 22nd Seminar on Current Trends in Theory and Practice of Informatics

Recurrent Neural Network Architectures: An Overview

Adaptive Processing of Sequences and Data Structures, International Summer School on Neural Networks, "E.R. Caianiello"-Tutorial Lectures

Diagrammatic Methods for Deriving and Relating Temporal Neural Network Algorithms

Adaptive Processing of Sequences and Data Structures, International Summer School on Neural Networks, "E.R. Caianiello"-Tutorial Lectures

Gradient Based Learning Methods

Adaptive Processing of Sequences and Data Structures, International Summer School on Neural Networks, "E.R. Caianiello"-Tutorial Lectures

Long Short-Term Memory

Neural Computation

Including hints in training neural nets

Neural Computation

The dynamics of discrete-time computation, with application to recurrent neural networks and finite state machine extraction

Neural Computation

A smoothing regularizer for feedforward and recurrent neural networks

Neural Computation

Diagrammatic derivation of gradient algorithms for neural networks

Neural Computation

A convergence result for learning in recurrent neural networks

Neural Computation

Computational capabilities of recurrent NARX neural networks

IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics

Learning long-term dependencies in NARX recurrent neural networks

IEEE Transactions on Neural Networks

Supervised neural networks for the classification of structures

IEEE Transactions on Neural Networks

Fast training of recurrent networks based on the EM algorithm

IEEE Transactions on Neural Networks

A general framework for adaptive processing of data structures

IEEE Transactions on Neural Networks

Constructive learning of recurrent neural networks: limitations of recurrent cascade correlation and a simple solution

IEEE Transactions on Neural Networks

On the computational power of Elman-style recurrent networks

IEEE Transactions on Neural Networks