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ICML
2008
IEEE
16 years 4 months ago
An analysis of linear models, linear value-function approximation, and feature selection for reinforcement learning
We show that linear value-function approximation is equivalent to a form of linear model approximation. We then derive a relationship between the model-approximation error and the...
Ronald Parr, Lihong Li, Gavin Taylor, Christopher ...
ICML
2009
IEEE
16 years 4 months ago
Interactively optimizing information retrieval systems as a dueling bandits problem
We present an on-line learning framework tailored towards real-time learning from observed user behavior in search engines and other information retrieval systems. In particular, ...
Yisong Yue, Thorsten Joachims
ICML
2008
IEEE
16 years 4 months ago
Modeling interleaved hidden processes
Hidden Markov models assume that observations in time series data stem from some hidden process that can be compactly represented as a Markov chain. We generalize this model by as...
Niels Landwehr
134
Voted
ICML
2008
IEEE
16 years 4 months ago
Learning to classify with missing and corrupted features
After a classifier is trained using a machine learning algorithm and put to use in a real world system, it often faces noise which did not appear in the training data. Particularl...
Ofer Dekel, Ohad Shamir
ICML
2008
IEEE
16 years 4 months ago
Fast nearest neighbor retrieval for bregman divergences
We present a data structure enabling efficient nearest neighbor (NN) retrieval for bregman divergences. The family of bregman divergences includes many popular dissimilarity measu...
Lawrence Cayton