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» Approximation and limiting behavior of random models
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STACS
1999
Springer
13 years 11 months ago
A Complete and Tight Average-Case Analysis of Learning Monomials
Abstract. We advocate to analyze the average complexity of learning problems. An appropriate framework for this purpose is introduced. Based on it we consider the problem of learni...
Rüdiger Reischuk, Thomas Zeugmann
SASO
2008
IEEE
14 years 1 months ago
Empirical Characterization of Discretization Error in Gradient-Based Algorithms
Many self-organizing and self-adaptive systems use the biologically inspired “gradient” primitive, in which each device in a network estimates its distance to the closest devi...
Jonathan Bachrach, Jacob Beal, Joshua Horowitz, Da...
CVPR
2001
IEEE
14 years 9 months ago
Affine Arithmetic Based Estimation of Cue Distributions in Deformable Model Tracking
In this paper we describe a statistical method for the integration of an unlimited number of cues within a deformable model framework. We treat each cue as a random variable, each...
Siome Goldenstein, Christian Vogler, Dimitris N. M...
BMCBI
2008
153views more  BMCBI 2008»
13 years 7 months ago
Estimating the size of the solution space of metabolic networks
Background: Cellular metabolism is one of the most investigated system of biological interactions. While the topological nature of individual reactions and pathways in the network...
Alfredo Braunstein, Roberto Mulet, Andrea Pagnani
CGA
1999
13 years 7 months ago
Dynamics Modeling and Culling
emsintovirtualenvironments,whileabstracting the modeling process as much as possible. To achieve efficiency,weconcentrateoncullingdynamicalsystems: if the system is not in view, we...
Stephen Chenney, Jeffrey Ichnowski, David A. Forsy...