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» Dynamic power management using machine learning
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126
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ICML
2006
IEEE
16 years 4 months ago
Nonstationary kernel combination
The power and popularity of kernel methods stem in part from their ability to handle diverse forms of structured inputs, including vectors, graphs and strings. Recently, several m...
Darrin P. Lewis, Tony Jebara, William Stafford Nob...
171
Voted
ESWA
2008
169views more  ESWA 2008»
15 years 3 months ago
Predicting opponent's moves in electronic negotiations using neural networks
Electronic negotiation experiments provide a rich source of information about relationships between the negotiators, their individual actions, and the negotiation dynami...
Réal Carbonneau, Gregory E. Kersten, Rustam...
137
Voted
CC
2006
Springer
124views System Software» more  CC 2006»
15 years 7 months ago
Hybrid Optimizations: Which Optimization Algorithm to Use?
We introduce a new class of compiler heuristics: hybrid optimizations. Hybrid optimizations choose dynamically at compile time which optimization algorithm to apply from a set of d...
John Cavazos, J. Eliot B. Moss, Michael F. P. O'Bo...
131
Voted
SIGLEX
1991
15 years 7 months ago
Conventional Metaphor and the Lexicon
Metaphor and other forms of non-literal language are essential parts of language which have direct bearing on theories of lexical semantics. Neither narrow theories of lexical sem...
James H. Martin
133
Voted
ICML
2010
IEEE
15 years 4 months ago
Boosting Classifiers with Tightened L0-Relaxation Penalties
We propose a novel boosting algorithm which improves on current algorithms for weighted voting classification by striking a better balance between classification accuracy and the ...
Noam Goldberg, Jonathan Eckstein