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NN
2000
Springer
192views Neural Networks» more  NN 2000»
15 years 4 months ago
A new algorithm for learning in piecewise-linear neural networks
Piecewise-linear (PWL) neural networks are widely known for their amenability to digital implementation. This paper presents a new algorithm for learning in PWL networks consistin...
Emad Gad, Amir F. Atiya, Samir I. Shaheen, Ayman E...
IS
2010
15 years 1 months ago
Multicriteria reinforcement learning based on a Russian doll method for network routing
The routing in communication networks is typically a multicriteria decision making (MCDM) problem. However, setting the parameters of most used MCDM methods to fit the preferences ...
Alain Pétrowski, Farouk Aissanou, Ilham Ben...
CVPR
2011
IEEE
15 years 1 months ago
Active Learning for Piecewise Planar 3D Reconstruction
In this work, we present an active-learning algorithm for piecewise planar 3D reconstruction of a scene. While previous interactive algorithms require the user to provide tedious i...
Adarsh Kowdle, Yao-Jen Chang, Andrew Gallagher, Ts...
ICCV
2011
IEEE
14 years 4 months ago
Perturb-and-MAP Random Fields: Using Discrete Optimization\\to Learn and Sample from Energy Models
We propose a novel way to induce a random field from an energy function on discrete labels. It amounts to locally injecting noise to the energy potentials, followed by finding t...
George Papandreou, Alan L. Yuille
VTS
2006
IEEE
108views Hardware» more  VTS 2006»
15 years 10 months ago
Bridging the Accuracy of Functional and Machine-Learning-Based Mixed-Signal Testing
Abstract— Numerous machine-learning-based test methodologies have been proposed in recent years as a fast alternative to the standard functional testing of mixed-signal/RF integr...
Haralampos-G. D. Stratigopoulos, Yiorgos Makris