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JMLR
2012
13 years 9 months ago
Contextual Bandit Learning with Predictable Rewards
Contextual bandit learning is a reinforcement learning problem where the learner repeatedly receives a set of features (context), takes an action and receives a reward based on th...
Alekh Agarwal, Miroslav Dudík, Satyen Kale,...
JMLR
2012
13 years 9 months ago
Domain Adaptation: A Small Sample Statistical Approach
We study the prevalent problem when a test distribution differs from the training distribution. We consider a setting where our training set consists of a small number of sample d...
Ruslan Salakhutdinov, Sham M. Kakade, Dean P. Fost...
JMLR
2012
13 years 9 months ago
On Sparse, Spectral and Other Parameterizations of Binary Probabilistic Models
This paper studies issues relating to the parameterization of probability distributions over binary data sets. Several such parameterizations of models for binary data are known, ...
David Buchman, Mark W. Schmidt, Shakir Mohamed, Da...
BMCBI
2007
167views more  BMCBI 2007»
15 years 7 months ago
AlzPharm: integration of neurodegeneration data using RDF
Background: Neuroscientists often need to access a wide range of data sets distributed over the Internet. These data sets, however, are typically neither integrated nor interopera...
Hugo Y. K. Lam, Luis N. Marenco, Tim Clark, Yong G...
SAC
2005
ACM
16 years 18 days ago
A hybrid approach for multiresolution modeling of large-scale scientific data
Simulations of complex scientific phenomena involve the execution of massively parallel computer programs. These simulation programs generate large-scale multidimensional data set...
Tina Eliassi-Rad, Terence Critchlow