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» Learning and Generalization with the Information Bottleneck
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ALT
2010
Springer
14 years 11 months ago
Bayesian Active Learning Using Arbitrary Binary Valued Queries
We explore a general Bayesian active learning setting, in which the learner can ask arbitrary yes/no questions. We derive upper and lower bounds on the expected number of queries r...
Liu Yang, Steve Hanneke, Jaime G. Carbonell
UAI
2004
14 years 11 months ago
The Minimum Information Principle for Discriminative Learning
Exponential models of distributions are widely used in machine learning for classification and modelling. It is well known that they can be interpreted as maximum entropy models u...
Amir Globerson, Naftali Tishby
ACL
2009
14 years 7 months ago
Word or Phrase? Learning Which Unit to Stress for Information Retrieval
The use of phrases in retrieval models has been proven to be helpful in the literature, but no particular research addresses the problem of discriminating phrases that are likely ...
Young-In Song, Jung-Tae Lee, Hae-Chang Rim
ISCA
2006
IEEE
138views Hardware» more  ISCA 2006»
15 years 3 months ago
Learning-Based SMT Processor Resource Distribution via Hill-Climbing
The key to high performance in Simultaneous Multithreaded (SMT) processors lies in optimizing the distribution of shared resources to active threads. Existing resource distributio...
Seungryul Choi, Donald Yeung
COLT
2006
Springer
15 years 1 months ago
Maximum Entropy Distribution Estimation with Generalized Regularization
Abstract. We present a unified and complete account of maximum entropy distribution estimation subject to constraints represented by convex potential functions or, alternatively, b...
Miroslav Dudík, Robert E. Schapire