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CVPR
2003
IEEE
16 years 8 months ago
An Efficient Approach to Learning Inhomogeneous Gibbs Model
Inhomogeneous Gibbs model (IGM) [4] is an effective maximum entropy model in characterizing complex highdimensional distributions. However, its training process is so slow that th...
Ziqiang Liu, Hong Chen, Heung-Yeung Shum
SIAMSC
2011
151views more  SIAMSC 2011»
15 years 1 months ago
Inexact Newton Methods with Restricted Additive Schwarz Based Nonlinear Elimination for Problems with High Local Nonlinearity
The classical inexact Newton algorithm is an efficient and popular technique for solving large sparse nonlinear system of equations. When the nonlinearities in the system are wellb...
Xiao-Chuan Cai, Xuefeng Li
GECCO
2006
Springer
188views Optimization» more  GECCO 2006»
15 years 9 months ago
Dynamic multi-objective optimization with evolutionary algorithms: a forward-looking approach
This work describes a forward-looking approach for the solution of dynamic (time-changing) problems using evolutionary algorithms. The main idea of the proposed method is to combi...
Iason Hatzakis, David Wallace
ICASSP
2011
IEEE
14 years 9 months ago
The Rotational Lasso
This paper presents a sparse approach of solving the onesided Procrustes problem with special orthogonal constraint. By leveraging a planar decomposition common to all rotation ma...
Alexander Lorbert, Peter J. Ramadge
ASPDAC
2009
ACM
161views Hardware» more  ASPDAC 2009»
16 years 17 days ago
Risk aversion min-period retiming under process variations
— Recent advances in statistical timing analysis (SSTA) achieve great success in computing arrival times under variations by extending sum and maximum operations to random variab...
Jia Wang, Hai Zhou