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EMNLP
2008
14 years 11 months ago
Complexity of Finding the BLEU-optimal Hypothesis in a Confusion Network
Confusion networks are a simple representation of multiple speech recognition or translation hypotheses in a machine translation system. A typical operation on a confusion network...
Gregor Leusch, Evgeny Matusov, Hermann Ney
UAI
1998
14 years 11 months ago
Flexible Decomposition Algorithms for Weakly Coupled Markov Decision Problems
This paper presents two new approaches to decomposing and solving large Markov decision problems (MDPs), a partial decoupling method and a complete decoupling method. In these app...
Ronald Parr
CORR
2010
Springer
253views Education» more  CORR 2010»
14 years 10 months ago
Fast Inference in Sparse Coding Algorithms with Applications to Object Recognition
Adaptive sparse coding methods learn a possibly overcomplete set of basis functions, such that natural image patches can be reconstructed by linearly combining a small subset of t...
Koray Kavukcuoglu, Marc'Aurelio Ranzato, Yann LeCu...
HEURISTICS
2006
95views more  HEURISTICS 2006»
14 years 9 months ago
Hard and soft constraints for reasoning about qualitative conditional preferences
Many real life optimization problems are defined in terms of both hard and soft constraints, and qualitative conditional preferences. However, there is as yet no single framework f...
Carmel Domshlak, Steven David Prestwich, Francesca...
IANDC
2006
86views more  IANDC 2006»
14 years 9 months ago
Table design in dynamic programming
Dynamic Programming solves combinatorial optimization problems by recursive decomposition and tabulation of intermediate results. The first step in the design of a dynamic program...
Peter Steffen, Robert Giegerich