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172
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COLT
2005
Springer
16 years 5 days ago
2005
Springer
We consider the problem of learning mixtures of distributions via spectral methods and derive a tight characterization of when such methods are useful. Specifically, given a mixt...
170
Voted
KDD
1999
ACM
15 years 11 months ago
1999
ACM
In this paper a concern about the accuracy (as a function of parallelism) of a certain class of distributed learning algorithms is raised, and one proposed improvement is illustrat...
185
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DAWAK
2006
Springer
15 years 10 months ago
2006
Springer
Abstract. There is an urgent need for sound approaches to integrative and collaborative analysis of large, autonomous (and hence, inevitably semantically heterogeneous) data source...
169
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ICML
2010
IEEE
15 years 7 months ago
2010
IEEE
Standard Reinforcement Learning (RL) aims to optimize decision-making rules in terms of the expected return. However, especially for risk-management purposes, other criteria such ...
198
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ACL
2012
13 years 9 months ago
2012
With a few exceptions, discriminative training in statistical machine translation (SMT) has been content with tuning weights for large feature sets on small development data. Evid...