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» Approximate algorithms for neural-Bayesian approaches
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ISAAC
2003
Springer
129views Algorithms» more  ISAAC 2003»
15 years 3 months ago
Polynomial Time Approximate Sampler for Discretized Dirichlet Distribution
Abstract. In this paper, we propose a Markov chain for sampling a random vector distributed according to a discretized Dirichlet distribution. We show that our Markov chain is rapi...
Tomomi Matsui, Mitsuo Motoki, Naoyuki Kamatani
ICASSP
2011
IEEE
14 years 1 months ago
Langevin and hessian with fisher approximation stochastic sampling for parameter estimation of structured covariance
We have studied two efficient sampling methods, Langevin and Hessian adapted Metropolis Hastings (MH), applied to a parameter estimation problem of the mathematical model (Lorent...
Cornelia Vacar, Jean-François Giovannelli, ...
CHARME
1997
Springer
105views Hardware» more  CHARME 1997»
15 years 1 months ago
Simulation-based verification of network protocols performance
Formal verification techniques need to deal with the complexity of the systems rified. Most often, this problem is solved by taking an abstract model of the system and aiming at a...
Mario Baldi, Fulvio Corno, Maurizio Rebaudengo, Pa...
BMCBI
2010
131views more  BMCBI 2010»
14 years 10 months ago
A comparison of approximation techniques for variance-based sensitivity analysis of biochemical reaction systems
Background: Sensitivity analysis is an indispensable tool for the analysis of complex systems. In a recent paper, we have introduced a thermodynamically consistent variance-based ...
Hong-Xuan Zhang, John Goutsias
TSP
2008
115views more  TSP 2008»
14 years 9 months ago
Approximation Bounds for Semidefinite Relaxation of Max-Min-Fair Multicast Transmit Beamforming Problem
Consider a downlink multicast scenario where a base station equipped with multiple antennas wishes to simultaneously broadcast a number of signals to some given groups of users ove...
Tsung-Hui Chang, Zhi-Quan Luo, Chong-Yung Chi