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» A Model Selection Approach for Local Learning
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EMNLP
2008
13 years 9 months ago
Maximum Entropy based Rule Selection Model for Syntax-based Statistical Machine Translation
This paper proposes a novel maximum entropy based rule selection (MERS) model for syntax-based statistical machine translation (SMT). The MERS model combines local contextual info...
Qun Liu, Zhongjun He, Yang Liu, Shouxun Lin
ICCV
2009
IEEE
1318views Computer Vision» more  ICCV 2009»
15 years 17 days ago
Non-Local Sparse Models for Image Restoration
We propose in this paper to unify two different ap- proaches to image restoration: On the one hand, learning a basis set (dictionary) adapted to sparse signal descriptions has p...
Julien Mairal, Francis Bach, Jean Ponce, Guillermo...
ICASSP
2011
IEEE
12 years 11 months ago
A kernelized maximal-figure-of-merit learning approach based on subspace distance minimization
We propose a kernelized maximal-figure-of-merit (MFoM) learning approach to efficiently training a nonlinear model using subspace distance minimization. In particular, a fixed,...
Byungki Byun, Chin-Hui Lee
GECCO
2007
Springer
144views Optimization» more  GECCO 2007»
13 years 11 months ago
Mixing independent classifiers
In this study we deal with the mixing problem, which concerns combining the prediction of independently trained local models to form a global prediction. We deal with it from the ...
Jan Drugowitsch, Alwyn Barry
EUROPAR
2011
Springer
12 years 7 months ago
Model-Driven Tile Size Selection for DOACROSS Loops on GPUs
DOALL loops are tiled to exploit DOALL parallelism and data locality on GPUs. In contrast, due to loop-carried dependences, DOACROSS loops must be skewed first in order to make ti...
Peng Di, Jingling Xue