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» Approximation algorithms for budgeted learning problems
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SODA
2007
ACM
145views Algorithms» more  SODA 2007»
13 years 10 months ago
Aggregation of partial rankings, p-ratings and top-m lists
We study the problem of aggregating partial rankings. This problem is motivated by applications such as meta-searching and information retrieval, search engine spam fighting, e-c...
Nir Ailon
IJCNN
2006
IEEE
14 years 2 months ago
Learning to Rank by Maximizing AUC with Linear Programming
— Area Under the ROC Curve (AUC) is often used to evaluate ranking performance in binary classification problems. Several researchers have approached AUC optimization by approxi...
Kaan Ataman, W. Nick Street, Yi Zhang
SIAMCOMP
2011
13 years 3 months ago
The Chow Parameters Problem
Abstract. In the 2nd Annual FOCS (1961), Chao-Kong Chow proved that every Boolean threshold function is uniquely determined by its degree-0 and degree-1 Fourier coefficients. These...
Ryan O'Donnell, Rocco A. Servedio
ESANN
2001
13 years 10 months ago
Learning fault-tolerance in Radial Basis Function Networks
This paper describes a method of supervised learning based on forward selection branching. This method improves fault tolerance by means of combining information related to general...
Xavier Parra, Andreu Català
NN
2000
Springer
192views Neural Networks» more  NN 2000»
13 years 8 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...