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» Approximation schemes for the Min-Max Starting Time Problem
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NN
2000
Springer
192views Neural Networks» more  NN 2000»
13 years 7 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...
SIAMSC
2008
106views more  SIAMSC 2008»
13 years 7 months ago
Finite Volume Simulation of the Geostrophic Adjustment in a Rotating Shallow-Water System
The goal of this article is to simulate rotating flows of shallow layers of fluid by means of finite volume numerical schemes. More precisely, we focus on the simulation of the geo...
Manuel J. Castro, Juan Antonio López, Carlo...
COMPGEOM
2011
ACM
12 years 11 months ago
Persistence-based clustering in riemannian manifolds
We present a clustering scheme that combines a mode-seeking phase with a cluster merging phase in the corresponding density map. While mode detection is done by a standard graph-b...
Frédéric Chazal, Leonidas J. Guibas,...
CORR
2010
Springer
190views Education» more  CORR 2010»
13 years 7 months ago
Bidimensionality and EPTAS
Bidimensionality theory appears to be a powerful framework for the development of metaalgorithmic techniques. It was introduced by Demaine et al. [J. ACM 2005 ] as a tool to obtai...
Fedor V. Fomin, Daniel Lokshtanov, Venkatesh Raman...
SIGMOD
2009
ACM
171views Database» more  SIGMOD 2009»
14 years 7 months ago
GAMPS: compressing multi sensor data by grouping and amplitude scaling
We consider the problem of collectively approximating a set of sensor signals using the least amount of space so that any individual signal can be efficiently reconstructed within...
Sorabh Gandhi, Suman Nath, Subhash Suri, Jie Liu