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» Optimal robust expensive optimization is tractable
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NIPS
2008
13 years 8 months ago
Partially Observed Maximum Entropy Discrimination Markov Networks
Learning graphical models with hidden variables can offer semantic insights to complex data and lead to salient structured predictors without relying on expensive, sometime unatta...
Jun Zhu, Eric P. Xing, Bo Zhang
AIPS
2010
13 years 7 months ago
Iterative Learning of Weighted Rule Sets for Greedy Search
Greedy search is commonly used in an attempt to generate solutions quickly at the expense of completeness and optimality. In this work, we consider learning sets of weighted actio...
Yuehua Xu, Alan Fern, Sung Wook Yoon
CCE
2007
13 years 7 months ago
Adaptive optimisation of noisy black-box functions inherent in microscopic models
For systems where exact constitutive relations are unknown, a microscopic level description can be alternatively used. As microscopic simulations are computationally expensive, th...
Eddie Davis, Marianthi G. Ierapetritou
JSAC
2006
199views more  JSAC 2006»
13 years 7 months ago
IDES: An Internet Distance Estimation Service for Large Networks
The responsiveness of networked applications is limited by communications delays, making network distance an important parameter in optimizing the choice of communications peers. S...
Yun Mao, Lawrence K. Saul, Jonathan M. Smith
PPL
2010
117views more  PPL 2010»
13 years 2 months ago
Neighborhood Structures for GPU-Based Local Search Algorithms
Local search (LS) algorithms are among the most powerful techniques for solving computationally hard problems in combinatorial optimization. These algorithms could be viewed as &q...
Thé Van Luong, Nouredine Melab, El-Ghazali ...