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PR
2006
89views more  PR 2006»
15 years 3 months ago
Gaussian fields for semi-supervised regression and correspondence learning
Gaussian fields (GF) have recently received considerable attention for dimension reduction and semi-supervised classification. In this paper we show how the GF framework can be us...
Jakob J. Verbeek, Nikos A. Vlassis
SODA
2001
ACM
166views Algorithms» more  SODA 2001»
15 years 4 months ago
Better approximation algorithms for bin covering
Bin covering takes as input a list of items with sizes in (0 1) and places them into bins of unit demand so as to maximize the number of bins whose demand is satis ed. This is in ...
János Csirik, David S. Johnson, Claire Keny...
LION
2010
Springer
190views Optimization» more  LION 2010»
15 years 7 months ago
Algorithm Selection as a Bandit Problem with Unbounded Losses
Abstract. Algorithm selection is typically based on models of algorithm performance learned during a separate offline training sequence, which can be prohibitively expensive. In r...
Matteo Gagliolo, Jürgen Schmidhuber
CORR
2010
Springer
127views Education» more  CORR 2010»
15 years 3 months ago
Online Algorithms for the Multi-Armed Bandit Problem with Markovian Rewards
We consider the classical multi-armed bandit problem with Markovian rewards. When played an arm changes its state in a Markovian fashion while it remains frozen when not played. Th...
Cem Tekin, Mingyan Liu
NIPS
1998
15 years 4 months ago
SMEM Algorithm for Mixture Models
When learning a mixture model, we suffer from the local optima and model structure determination problems. In this paper, we present a method for simultaneously solving these prob...
Naonori Ueda, Ryohei Nakano, Zoubin Ghahramani, Ge...