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CORR
2010
Springer
130views Education» more  CORR 2010»
14 years 11 months ago
Approximated Structured Prediction for Learning Large Scale Graphical Models
In this paper we propose an approximated structured prediction framework for large scale graphical models and derive message-passing algorithms for learning their parameters effic...
Tamir Hazan, Raquel Urtasun
NN
2000
Springer
192views Neural Networks» more  NN 2000»
14 years 11 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...
MOC
2002
131views more  MOC 2002»
14 years 11 months ago
Some baby-step giant-step algorithms for the low hamming weight discrete logarithm problem
In this paper, we present several baby-step giant-step algorithms for the low hamming weight discrete logarithm problem. In this version of the discrete log problem, we are require...
Douglas R. Stinson
GIS
2002
ACM
14 years 11 months ago
Search algorithms for multiway spatial joins
This papers deals with multiway spatial joins when (i) there is limited time for query processing and the goal is to retrieve the best possible solutions within this limit (ii) the...
Dimitris Papadias, Dinos Arkoumanis
SODA
2008
ACM
156views Algorithms» more  SODA 2008»
15 years 1 months ago
Approximating TSP on metrics with bounded global growth
The Traveling Salesman Problem (TSP) is a canonical NP-complete problem which is known to be MAXSNP hard even on Euclidean metrics (of high dimensions) [40]. In order to circumven...
T.-H. Hubert Chan, Anupam Gupta