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COLT
2006
Springer
13 years 11 months ago
Teaching Randomized Learners
Abstract. The present paper introduces a new model for teaching randomized learners. Our new model, though based on the classical teaching dimension model, allows to study the infl...
Frank J. Balbach, Thomas Zeugmann
ESANN
2003
13 years 8 months ago
Approximation of Function by Adaptively Growing Radial Basis Function Neural Networks
In this paper a neural network for approximating function is described. The activation functions of the hidden nodes are the Radial Basis Functions (RBF) whose parameters are learn...
Jianyu Li, Siwei Luo, Yingjian Qi
PRL
2011
13 years 2 months ago
Efficient approximate Regularized Least Squares by Toeplitz matrix
Machine Learning based on the Regularized Least Square (RLS) model requires one to solve a system of linear equations. Direct-solution methods exhibit predictable complexity and s...
Sergio Decherchi, Paolo Gastaldo, Rodolfo Zunino
JMLR
2010
141views more  JMLR 2010»
13 years 2 months ago
FastInf: An Efficient Approximate Inference Library
The FastInf C++ library is designed to perform memory and time efficient approximate inference in large-scale discrete undirected graphical models. The focus of the library is pro...
Ariel Jaimovich, Ofer Meshi, Ian McGraw, Gal Elida...
AAAI
2012
11 years 9 months ago
Dynamic Matching via Weighted Myopia with Application to Kidney Exchange
In many dynamic matching applications—especially high-stakes ones—the competitive ratios of prior-free online algorithms are unacceptably poor. The algorithm should take distr...
John P. Dickerson, Ariel D. Procaccia, Tuomas Sand...