Add to ORKGTo appear in the Handoobk of Brain Theory and Neural Networks, Michael Arbib, Ed. Prepared within the space and reference limitations of the Handbook Grace Wahba Generalization and Regularization in Nonlinear Learning Systems 1
The theory developed in Poggio and Girosi (1989) shows the equivalence between regularization and ...
Abstract: In this paper we present a regularization approach to the training of all the network weig...
The paper considers the problem of regularization of automatic stable training of networks of artifi...
Learning with generalization can be modeled using regularization, which was developed for a search o...
This thesis investigates the generalization problem in artificial neural networks, attacking it from...
This thesis presents a new theory of generalization in neural network types of learning machines. Th...
SIGLETIB Hannover: RN 7349 (411) / FIZ - Fachinformationszzentrum Karlsruhe / TIB - Technische Infor...
We study the evolution of the generalization ability of a simple linear per-ceptron with N inputs wh...
venkateshGee.upenn.edu This paper presents a rigorous characterization of how a general nonlinear le...
A gradient learning method to regulate the trajectories of some nonlinear chaotic systems is propose...
Learning an input-output mapping from a set of examples, of the type that many neural networks hav...
. We introduce the concept of generalization for models of functional neuroactivation, and show how ...
Tag der mündlichen Prüfung: One of the most important features of natural as well as artificial ne...
Theoretical and computational justification is given for improved generalization when the training s...
Inspired by the adaptation phenomenon of neuronal firing, we propose the regularity normalization (R...
The theory developed in Poggio and Girosi (1989) shows the equivalence between regularization and ...
Abstract: In this paper we present a regularization approach to the training of all the network weig...
The paper considers the problem of regularization of automatic stable training of networks of artifi...
Learning with generalization can be modeled using regularization, which was developed for a search o...
This thesis investigates the generalization problem in artificial neural networks, attacking it from...
This thesis presents a new theory of generalization in neural network types of learning machines. Th...
SIGLETIB Hannover: RN 7349 (411) / FIZ - Fachinformationszzentrum Karlsruhe / TIB - Technische Infor...
We study the evolution of the generalization ability of a simple linear per-ceptron with N inputs wh...
venkateshGee.upenn.edu This paper presents a rigorous characterization of how a general nonlinear le...
A gradient learning method to regulate the trajectories of some nonlinear chaotic systems is propose...
Learning an input-output mapping from a set of examples, of the type that many neural networks hav...
. We introduce the concept of generalization for models of functional neuroactivation, and show how ...
Tag der mündlichen Prüfung: One of the most important features of natural as well as artificial ne...
Theoretical and computational justification is given for improved generalization when the training s...
Inspired by the adaptation phenomenon of neuronal firing, we propose the regularity normalization (R...
The theory developed in Poggio and Girosi (1989) shows the equivalence between regularization and ...
Abstract: In this paper we present a regularization approach to the training of all the network weig...
The paper considers the problem of regularization of automatic stable training of networks of artifi...