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» Approximate algorithms for neural-Bayesian approaches
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SIAMSC
2008
147views more  SIAMSC 2008»
14 years 10 months ago
Global and Finite Termination of a Two-Phase Augmented Lagrangian Filter Method for General Quadratic Programs
We present a two-phase algorithm for solving large-scale quadratic programs (QPs). In the first phase, gradient-projection iterations approximately minimize an augmented Lagrangian...
Michael P. Friedlander, Sven Leyffer
STOC
2012
ACM
221views Algorithms» more  STOC 2012»
13 years 16 days ago
From query complexity to computational complexity
We consider submodular optimization problems, and provide a general way of translating oracle inapproximability results arising from the symmetry gap technique to computational co...
Shahar Dobzinski, Jan Vondrák
ECCV
2002
Springer
15 years 12 months ago
Bayesian Self-Calibration of a Moving Camera
In this paper, a Bayesian self-calibration approach using sequential importance sampling (SIS) is proposed. Given a set of feature correspondences tracked through an image sequenc...
Gang Qian, Rama Chellappa
ICIP
2006
IEEE
15 years 11 months ago
Modulation Domain Features for Discriminating Infrared Targets and Backgrounds
For the first time, we compute modulation domain features for infrared targets and backgrounds, including dominant modulations that characterize the local texture contrast, orient...
Chuong T. Nguyen, Joseph P. Havlicek
ICASSP
2008
IEEE
15 years 4 months ago
Discriminative learning for optimizing detection performance in spoken language recognition
We propose novel approaches for optimizing the detection performance in spoken language recognition. Two objective functions are designed to directly relate model parameters to tw...
Donglai Zhu, Haizhou Li, Bin Ma, Chin-Hui Lee