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» Minimization of an M-convex Function
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APPROX
2005
Springer
111views Algorithms» more  APPROX 2005»
16 years 4 days ago
Sampling Bounds for Stochastic Optimization
A large class of stochastic optimization problems can be modeled as minimizing an objective function f that depends on a choice of a vector x ∈ X, as well as on a random external...
Moses Charikar, Chandra Chekuri, Martin Pál
SWAT
2004
Springer
120views Algorithms» more  SWAT 2004»
15 years 12 months ago
Matching Polyhedral Terrains Using Overlays of Envelopes
For a collection F of d-variate piecewise linear functions of overall combinatorial complexity n, the lower envelope E(F) of F is the pointwise minimum of these functions. The min...
Vladlen Koltun, Carola Wenk
AHSWN
2008
92views more  AHSWN 2008»
15 years 6 months ago
The (k, l) Coredian Tree for Ad Hoc Networks
In this paper, we present a new efficient strategy for constructing a wireless tree network containing n nodes of diameter while satisfying the QoS requirements such as bandwidth...
Amit Dvir, Michael Segal
PAMI
2008
162views more  PAMI 2008»
15 years 6 months ago
Bayes Optimality in Linear Discriminant Analysis
We present an algorithm which provides the one-dimensional subspace where the Bayes error is minimized for the C class problem with homoscedastic Gaussian distributions. Our main ...
Onur C. Hamsici, Aleix M. Martínez
TSP
2008
116views more  TSP 2008»
15 years 6 months ago
Nonideal Sampling and Regularization Theory
Shannon's sampling theory and its variants provide effective solutions to the problem of reconstructing a signal from its samples in some "shift-invariant" space, wh...
Sathish Ramani, Dimitri Van De Ville, Thierry Blu,...