In geographic (or geometric) routing, messages are expected to route in a greedy manner: the current node always forwards a message to its neighbor node that is closest to the des...
Abstract Image alignment has been a long standing problem in computer vision. Parameterized Appearance Models (PAMs) such as the Lucas-Kanade method, Eigentracking, and Active Appe...
In this paper, we examine the problem of locating an object in an image when size and rotation are unknown. Previous work has shown that with known geometric parameters, an image r...
Roger M. Dufour, Eric L. Miller, Nikolas P. Galats...
—In this letter we point out that multilayer neural networks (MLP’s) with either sigmoidal units or radial basis functions can be given a canonical form with positive interunit...
Local minima and plateaus pose a serious problem in learning of neural networks. We investigate the hierarchical geometric structure of the parameter space of three-layer perceptr...
The Multidimensional Assignment Problem (MAP) is an NP-hard combinatorial optimization problem occurring in many applications, such as data association, target tracking, and resou...
Don A. Grundel, Pavlo A. Krokhmal, Carlos A. S. Ol...
We apply the method known as simulated annealing to the following problem in convex optimization: minimize a linear function over an arbitrary convex set, where the convex set is ...
Results of neural network learning are always subject to some variability, due to the sensitivity to initial conditions, to convergence to local minima, and, sometimes more dramat...
A biclustering algorithm, based on a greedy technique and enriched with a local search strategy to escape poor local minima, is proposed. The algorithm starts with an initial rand...
A new stochastic clustering algorithm is introduced that aims to locate all the local minima of a multidimensional continuous and differentiable function inside a bounded domain. ...