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FOCS
1992
IEEE
13 years 11 months ago
Maximizing Non-Linear Concave Functions in Fixed Dimension
Consider a convex set P in IRd and a piecewise polynomial concave function F: P IR. Let A be an algorithm that given a point x IRd computes F(x) if x P, or returns a concave po...
Sivan Toledo
FCT
2007
Springer
13 years 11 months ago
On Approximating Optimal Weighted Lobbying, and Frequency of Correctness Versus Average-Case Polynomial Time
We investigate issues regarding two hard problems related to voting, the optimal weighted lobbying problem and the winner problem for Dodgson elections. Regarding the former, Chris...
Gábor Erdélyi, Lane A. Hemaspaandra,...
IJCAI
2001
13 years 9 months ago
R-MAX - A General Polynomial Time Algorithm for Near-Optimal Reinforcement Learning
R-max is a very simple model-based reinforcement learning algorithm which can attain near-optimal average reward in polynomial time. In R-max, the agent always maintains a complet...
Ronen I. Brafman, Moshe Tennenholtz
CORR
2008
Springer
129views Education» more  CORR 2008»
13 years 7 months ago
Polynomial Linear Programming with Gaussian Belief Propagation
Abstract--Interior-point methods are state-of-the-art algorithms for solving linear programming (LP) problems with polynomial complexity. Specifically, the Karmarkar algorithm typi...
Danny Bickson, Yoav Tock, Ori Shental, Danny Dolev
PAMI
2010
156views more  PAMI 2010»
13 years 6 months ago
An Adaptive and Stable Method for Fitting Implicit Polynomial Curves and Surfaces
—Representing 2D and 3D data sets with implicit polynomials (IPs) has been attractive because of its applicability to various computer vision issues. Therefore, many IP fitting m...
Bo Zheng, Jun Takamatsu, Katsushi Ikeuchi