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» Ontological Framework for Approximation
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EMNLP
2011
14 years 4 months ago
Approximate Scalable Bounded Space Sketch for Large Data NLP
We exploit sketch techniques, especially the Count-Min sketch, a memory, and time efficient framework which approximates the frequency of a word pair in the corpus without explic...
Amit Goyal, Hal Daumé III
CVPR
1998
IEEE
16 years 7 months ago
Markov Random Fields with Efficient Approximations
Markov Random Fields (MRF's) can be used for a wide variety of vision problems. In this paper we focus on MRF's with two-valued clique potentials, which form a generaliz...
Yuri Boykov, Olga Veksler, Ramin Zabih
159
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ICML
2005
IEEE
16 years 6 months ago
Learning as search optimization: approximate large margin methods for structured prediction
Mappings to structured output spaces (strings, trees, partitions, etc.) are typically learned using extensions of classification algorithms to simple graphical structures (eg., li...
Daniel Marcu, Hal Daumé III
SARA
2009
Springer
15 years 11 months ago
Some Interval Approximation Techniques for MINLP
MINLP problems are hard constrained optimization problems, with nonlinear constraints and mixed discrete continuous variables. They can be solved using a Branch-and-Bound scheme c...
Nicolas Berger, Laurent Granvilliers
WSC
2008
15 years 7 months ago
Approximate dynamic programming: Lessons from the field
Approximate dynamic programming is emerging as a powerful tool for certain classes of multistage stochastic, dynamic problems that arise in operations research. It has been applie...
Warren B. Powell