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» Approximation algorithms for budgeted learning problems
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UAI
1998
13 years 9 months ago
The Bayesian Structural EM Algorithm
In recent years there has been a flurry of works on learning Bayesian networks from data. One of the hard problems in this area is how to effectively learn the structure of a beli...
Nir Friedman
ICPR
2008
IEEE
14 years 9 months ago
A discrete-time parallel update algorithm for distributed learning
We present a distributed machine learning framework based on support vector machines that allows classification problems to be solved iteratively through parallel update algorithm...
Christian Bauckhage, Tansu Alpcan
AAAI
2007
13 years 10 months ago
Restart Schedules for Ensembles of Problem Instances
The mean running time of a Las Vegas algorithm can often be dramatically reduced by periodically restarting it with a fresh random seed. The optimal restart schedule depends on th...
Matthew J. Streeter, Daniel Golovin, Stephen F. Sm...
EUROCOLT
1999
Springer
14 years 23 days ago
Query by Committee, Linear Separation and Random Walks
Abstract. Recent works have shown the advantage of using Active Learning methods, such as the Query by Committee (QBC) algorithm, to various learning problems. This class of Algori...
Ran Bachrach, Shai Fine, Eli Shamir
ECCC
2008
98views more  ECCC 2008»
13 years 8 months ago
Public-Key Cryptosystems from the Worst-Case Shortest Vector Problem
We construct public-key cryptosystems that are secure assuming the worst-case hardness of approximating the minimum distance on n-dimensional lattices to within small poly(n) fact...
Chris Peikert