Add to ORKGRecurrent Cascade-Correlation (RCC) is a recurrent version of the Cascade-Correlation learning architecture of Fahlman and Lebiere [Fahlman, 1990]. RCC can learn from examples to map a sequence of inputs into a desired sequence of outputs. New hidden units with recurrent connections are added to the network one at a time, as they are needed during training. In effect, the network builds up a finite-state machine tailored specifically for the current problem. RCC retains the advantages of Cascade-Correlation: fast learning, good generalization, automatic construction of a near-minimal multi-layered network, and the ability to learn complex behaviors through a sequence of simple lessons. The power of RCC is demonstrated on two tasks: learning...
Multi-task learning (MTL) is an established method of inducing bias in neural network learning. It h...
Recurrent neural networks can simulate any finite state automata as well as any multi-stack Turing m...
The Cascade-Correlation learning algorithm constructs a multi-layer artificial neural network as it ...
It is often difficult to predict the optimal neural network size for a particular application. Const...
It is often difficult to predict the optimal neural network size for a particular application. Const...
It is often difficult to predict the optimal neural network size for a particular application, Const...
Cascade correlation (CC) constitutes a training method for neural networks which determines the weig...
Abstract: "Cascade-Correlation is a new architecture and supervised learning algorithm for artificia...
We explore a network architecture introduced by Elman (1988) for predicting successive elements of a...
Neural network modeling typically ignores the role of knowledge in learning by starting from random ...
We propose a Relational Neural Network defined as a special instance of the Recurrent Cascade Correl...
This study investigated the use of state-trace analysis (Bamber, 1979) when applied to computational...
An experimental investigation of the cascade-correlation network (CC) is carried out in different be...
CogSci 2012 - 34th annual meeting of the Cognitive Science Society, Sapporo, Japan, 1-4 August 2012T...
The ability to learn in dynamic, nonstationary environments without forgetting previous knowledge, a...
Multi-task learning (MTL) is an established method of inducing bias in neural network learning. It h...
Recurrent neural networks can simulate any finite state automata as well as any multi-stack Turing m...
The Cascade-Correlation learning algorithm constructs a multi-layer artificial neural network as it ...
It is often difficult to predict the optimal neural network size for a particular application. Const...
It is often difficult to predict the optimal neural network size for a particular application. Const...
It is often difficult to predict the optimal neural network size for a particular application, Const...
Cascade correlation (CC) constitutes a training method for neural networks which determines the weig...
Abstract: "Cascade-Correlation is a new architecture and supervised learning algorithm for artificia...
We explore a network architecture introduced by Elman (1988) for predicting successive elements of a...
Neural network modeling typically ignores the role of knowledge in learning by starting from random ...
We propose a Relational Neural Network defined as a special instance of the Recurrent Cascade Correl...
This study investigated the use of state-trace analysis (Bamber, 1979) when applied to computational...
An experimental investigation of the cascade-correlation network (CC) is carried out in different be...
CogSci 2012 - 34th annual meeting of the Cognitive Science Society, Sapporo, Japan, 1-4 August 2012T...
The ability to learn in dynamic, nonstationary environments without forgetting previous knowledge, a...
Multi-task learning (MTL) is an established method of inducing bias in neural network learning. It h...
Recurrent neural networks can simulate any finite state automata as well as any multi-stack Turing m...
The Cascade-Correlation learning algorithm constructs a multi-layer artificial neural network as it ...