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VLSISP
2011
358views Database» more  VLSISP 2011»
15 years 1 months ago
Accelerating Machine-Learning Algorithms on FPGAs using Pattern-Based Decomposition
Machine-learning algorithms are employed in a wide variety of applications to extract useful information from data sets, and many are known to suffer from superlinear increases in ...
Karthik Nagarajan, Brian Holland, Alan D. George, ...
ICPR
2008
IEEE
16 years 1 months ago
Determination of optimal metabolic pathways through a new learning algorithm
In the present article, we introduce a new method for identification of metabolic pathways in constraint based models that consider enzyme and substrate concentrations. It genera...
C. A. Murthy, Mouli Das, Rajat K. De, Subhasis Muk...
DAGM
2007
Springer
15 years 10 months ago
Efficient Learning of Neural Networks with Evolutionary Algorithms
Abstract. In this article we present EANT2, a method that creates neural networks (NNs) by evolutionary reinforcement learning. The structure of NNs is developed using mutation ope...
Nils T. Siebel, Jochen Krause, Gerald Sommer
IJCAI
2003
15 years 8 months ago
A Learning Algorithm for Localizing People Based on Wireless Signal Strength that Uses Labeled and Unlabeled Data
This paper summarizes a probabilistic approach for localizing people through the signal strengths of a wireless IEEE 802.11b network. Our approach uses data labeled by ground trut...
Sebastian Thrun, Geoffrey J. Gordon, Frank Pfennin...
ICCV
2007
IEEE
16 years 8 months ago
Limits of Learning-Based Superresolution Algorithms
Learning-based superresolution (SR) are popular SR techniques that use application dependent priors to infer the missing details in low resolution images (LRIs). However, their pe...
Zhouchen Lin, Junfeng He, Xiaoou Tang, Chi-Keung T...