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EOR
2010
101views more  EOR 2010»
13 years 2 months ago
A linear implementation of PACMAN
PACMAN (Passive and Active Compensability Multicriteria ANalysis) is a multiple criteria methodology based on a decision maker oriented notion of compensation, called compensabili...
Silvia Angilella, Alfio Giarlotta, Fabio Lamantia
APPROX
2005
Springer
150views Algorithms» more  APPROX 2005»
14 years 1 months ago
A Primal-Dual Approximation Algorithm for Partial Vertex Cover: Making Educated Guesses
We study the partial vertex cover problem. Given a graph G = (V, E), a weight function w : V → R+ , and an integer s, our goal is to cover all but s edges, by picking a set of v...
Julián Mestre
ECML
2006
Springer
13 years 11 months ago
Approximate Policy Iteration for Closed-Loop Learning of Visual Tasks
Abstract. Approximate Policy Iteration (API) is a reinforcement learning paradigm that is able to solve high-dimensional, continuous control problems. We propose to exploit API for...
Sébastien Jodogne, Cyril Briquet, Justus H....
RT
2004
Springer
14 years 1 months ago
All-Frequency Relighting of Non-Diffuse Objects using Separable BRDF Approximation
This paper presents a technique, based on pre-computed light transport and separable BRDF approximation, for interactive rendering of non-diffuse objects under all-frequency envir...
Rui Wang 0003, John Tran, David P. Luebke
SIAMSC
2010
141views more  SIAMSC 2010»
13 years 6 months ago
An Iterative Method for Edge-Preserving MAP Estimation When Data-Noise Is Poisson
In numerous applications of image processing, e.g. astronomical and medical imaging, data-noise is well-modeled by a Poisson distribution. This motivates the use of the negative-lo...
Johnathan M. Bardsley, John Goldes