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UAI
1997
14 years 11 months ago
A Bayesian Approach to Learning Bayesian Networks with Local Structure
Recently several researchers have investigated techniques for using data to learn Bayesian networks containing compact representations for the conditional probability distribution...
David Maxwell Chickering, David Heckerman, Christo...
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
ICML
2008
IEEE
15 years 10 months ago
Reinforcement learning in the presence of rare events
We consider the task of reinforcement learning in an environment in which rare significant events occur independently of the actions selected by the controlling agent. If these ev...
Jordan Frank, Shie Mannor, Doina Precup
IPM
2008
100views more  IPM 2008»
14 years 9 months ago
Query-level loss functions for information retrieval
Many machine learning technologies such as support vector machines, boosting, and neural networks have been applied to the ranking problem in information retrieval. However, since...
Tao Qin, Xu-Dong Zhang, Ming-Feng Tsai, De-Sheng W...
COLT
2008
Springer
14 years 11 months ago
Almost Tight Upper Bound for Finding Fourier Coefficients of Bounded Pseudo- Boolean Functions
A pseudo-Boolean function is a real-valued function defined on {0, 1}n . A k-bounded function is a pseudo-Boolean function that can be expressed as a sum of subfunctions each of w...
Sung-Soon Choi, Kyomin Jung, Jeong Han Kim