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JMLR
2010
125views more  JMLR 2010»
14 years 10 months ago
Maximum Likelihood in Cost-Sensitive Learning: Model Specification, Approximations, and Upper Bounds
The presence of asymmetry in the misclassification costs or class prevalences is a common occurrence in the pattern classification domain. While much interest has been devoted to ...
Jacek P. Dmochowski, Paul Sajda, Lucas C. Parra
ICASSP
2011
IEEE
14 years 7 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, ...
TSP
2010
14 years 10 months ago
Quasi-interpolation by means of filter-banks
We consider the problem of approximating a regular function f(t) from its samples, f(nT), taken in a uniform grid. Quasi-interpolation schemes approximate f(t) with a dilated versi...
Gerardo Pérez-Villalón
INFOCOM
2005
IEEE
15 years 9 months ago
Power assignment for k-connectivity in wireless ad hoc networks
— The problem Min-Power k-Connectivity seeks a power assignment to the nodes in a given wireless ad hoc network such that the produced network topology is k-connected and the tot...
Xiaohua Jia, Dongsoo Kim, Sam Makki, Peng-Jun Wan,...
166
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AAAI
2000
15 years 5 months ago
Depth-First Branch-and-Bound versus Local Search: A Case Study
Depth-first branch-and-bound (DFBnB) is a complete algorithm that is typically used to find optimal solutions of difficult combinatorial optimization problems. It can also be adap...
Weixiong Zhang