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ICPR
2008
IEEE
16 years 3 months ago
Semi-supervised learning on large complex simulations
Complex simulations can generate very large amounts of data stored disjointly across many local disks. Learning from this data can be problematic due to the difficulty of obtainin...
John Nicholas Korecki, Kevin W. Bowyer, Larry O. H...
ICML
2009
IEEE
16 years 2 months ago
Learning non-redundant codebooks for classifying complex objects
Codebook-based representations are widely employed in the classification of complex objects such as images and documents. Most previous codebook-based methods construct a single c...
Wei Zhang, Akshat Surve, Xiaoli Fern, Thomas G. Di...
109
Voted
TCC
2010
Springer
173views Cryptology» more  TCC 2010»
15 years 10 months ago
Bounds on the Sample Complexity for Private Learning and Private Data Release
Learning is a task that generalizes many of the analyses that are applied to collections of data, and in particular, collections of sensitive individual information. Hence, it is n...
Amos Beimel, Shiva Prasad Kasiviswanathan, Kobbi N...
ML
2002
ACM
128views Machine Learning» more  ML 2002»
15 years 1 months ago
A Simple Method for Generating Additive Clustering Models with Limited Complexity
Additive clustering was originally developed within cognitive psychology to enable the development of featural models of human mental representation. The representational flexibili...
Michael D. Lee
114
Voted
AAAI
1993
15 years 3 months ago
Complexity Analysis of Real-Time Reinforcement Learning
This paper analyzes the complexity of on-line reinforcement learning algorithms, namely asynchronous realtime versions of Q-learning and value-iteration, applied to the problem of...
Sven Koenig, Reid G. Simmons