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WSC
2008
13 years 11 months ago
On step sizes, stochastic shortest paths, and survival probabilities in Reinforcement Learning
Reinforcement Learning (RL) is a simulation-based technique useful in solving Markov decision processes if their transition probabilities are not easily obtainable or if the probl...
Abhijit Gosavi
STACS
2007
Springer
14 years 3 months ago
New Approximation Algorithms for Minimum Cycle Bases of Graphs
We consider the problem of computing an approximate minimum cycle basis of an undirected non-negative edge-weighted graph G with m edges and n vertices; the extension to directed ...
Telikepalli Kavitha, Kurt Mehlhorn, Dimitrios Mich...
GECCO
2007
Springer
215views Optimization» more  GECCO 2007»
14 years 1 months ago
Finding safety errors with ACO
Model Checking is a well-known and fully automatic technique for checking software properties, usually given as temporal logic formulae on the program variables. Most model checke...
Enrique Alba, J. Francisco Chicano
IJCAI
2003
13 years 10 months ago
A Planning Algorithm for Predictive State Representations
We address the problem of optimally controlling stochastic environments that are partially observable. The standard method for tackling such problems is to define and solve a Part...
Masoumeh T. Izadi, Doina Precup
ICCV
2005
IEEE
14 years 11 months ago
Quasiconvex Optimization for Robust Geometric Reconstruction
Geometric reconstruction problems in computer vision are often solved by minimizing a cost function that combines the reprojection errors in the 2D images. In this paper, we show t...
Qifa Ke, Takeo Kanade