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» On the Convergence of Bound Optimization Algorithms
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COLT
2000
Springer
13 years 12 months ago
Estimation and Approximation Bounds for Gradient-Based Reinforcement Learning
We model reinforcement learning as the problem of learning to control a Partially Observable Markov Decision Process (  ¢¡¤£¦¥§  ), and focus on gradient ascent approache...
Peter L. Bartlett, Jonathan Baxter
CASC
2009
Springer
157views Mathematics» more  CASC 2009»
14 years 2 months ago
On the Complexity of Reliable Root Approximation
This work addresses the problem of computing a certified ǫ-approximation of all real roots of a square-free integer polynomial. We proof an upper bound for its bit complexity, b...
Michael Kerber
GECCO
2008
Springer
152views Optimization» more  GECCO 2008»
13 years 8 months ago
Designing EDAs by using the elitist convergent EDA concept and the boltzmann distribution
This paper presents a theoretical definition for designing EDAs called Elitist Convergent Estimation of Distribution Algorithm (ECEDA), and a practical implementation: the Boltzm...
Sergio Ivvan Valdez Peña, Arturo Hern&aacut...
INFOCOM
2007
IEEE
14 years 1 months ago
Randomized k-Coverage Algorithms For Dense Sensor Networks
— We propose new algorithms to achieve k-coverage in dense sensor networks. In such networks, covering sensor locations approximates covering the whole area. However, it has been...
Mohamed Hefeeda, M. Bagheri
CP
2008
Springer
13 years 9 months ago
Revisiting the Upper Bounding Process in a Safe Branch and Bound Algorithm
Abstract. Finding feasible points for which the proof succeeds is a critical issue in safe Branch and Bound algorithms which handle continuous problems. In this paper, we introduce...
Alexandre Goldsztejn, Yahia Lebbah, Claude Michel,...