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TMI
2010
298views more  TMI 2010»
13 years 2 months ago
An Efficient Numerical Method for General Lp Regularization in Fluorescence Molecular Tomography
Abstract--Reconstruction algorithms for fluorescence tomography have to address two crucial issues : (i) the ill-posedness of the reconstruction problem, (ii) the large scale of nu...
Jean-Charles Baritaux, Kai Hassler, Michael Unser
GECCO
2009
Springer
111views Optimization» more  GECCO 2009»
14 years 2 months ago
Evolving quorum sensing in digital organisms
For centuries it was thought that bacteria live asocial lives. However, recent discoveries show many species of bacteria communicate in order to perform tasks previously thought t...
Benjamin E. Beckmann, Philip K. McKinley
PAMI
2008
161views more  PAMI 2008»
13 years 7 months ago
TRUST-TECH-Based Expectation Maximization for Learning Finite Mixture Models
The Expectation Maximization (EM) algorithm is widely used for learning finite mixture models despite its greedy nature. Most popular model-based clustering techniques might yield...
Chandan K. Reddy, Hsiao-Dong Chiang, Bala Rajaratn...
CORR
2008
Springer
98views Education» more  CORR 2008»
13 years 7 months ago
An Information-Theoretical View of Network-Aware Malware Attacks
This work investigates three aspects: (a) a network vulnerability as the non-uniform vulnerable-host distribution, (b) threats, i.e., intelligent malwares that exploit such a vulne...
Zesheng Chen, Chuanyi Ji
ACL
2006
13 years 9 months ago
Approximation Lasso Methods for Language Modeling
Lasso is a regularization method for parameter estimation in linear models. It optimizes the model parameters with respect to a loss function subject to model complexities. This p...
Jianfeng Gao, Hisami Suzuki, Bin Yu