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From Infinite to Finite Programs: Explicit Error Bounds with Applications to Approximate Dynamic Programming

Publications associées (89)

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Barycentric Bounds in Stochastic Programming: Theory and Application

Daniel Kuhn

The design and analysis of efficient approximation schemes are of fundamental importance in stochastic programming research. Bounding approximations are particularly popular for providing strict error bounds that can be made small by using partitioning tec ...

Springer New York2011

Mean field for Markov Decision Processes: from Discrete to Continuous Optimization

Jean-Yves Le Boudec, Nicolas Gabriel Gast

We study the convergence of Markov Decision Processes made of a large number of objects to optimization problems on ordinary differential equations (ODE). We show that the optimal reward of such a Markov Decision Process, satisfying a Bellman equation, con ...

2010

A natural-norm Successive Constraint Method for inf-sup lower bounds

Jan Sickmann Hesthaven, Yixing Chen

We present a new approach for the construction of lower bounds for the inf-sup stability constants required in a posteriori error analysis of reduced basis approximations to affinely parametrized partial differential equations. We combine the ``linearized' ...

Elsevier2010

Markov decision processes for services opportunity pipeline optimization

Aurélie Glerum

The dynamics of sales opportunities can be modelled by a Markov Decision Process. The latter can be solved by using dynamic programming and assigns to each state an optimal action. In this project, states are modelled by the number of opportunities at five ...

2010

A Mathematical Model for the Locomotive Refueling Problem

Prem Kumar

This problem corresponds to refueling locomotives at different station yards during the course of its journey. Locomotive tanks have a fixed fuel capacity and prices of fuel vary across yards. In addition, there is a fixed cost for hiring a refueling truck ...

2010

Multiple Object Tracking using Flow Linear Programming

Pascal Fua, François Fleuret, Jérôme Berclaz

Multi-object tracking can be achieved by detecting objects in individual frames and then linking detections across frames. Such an approach can be made very robust to the occasional detection failure: If an object is not detected in a frame but is in previ ...

2009

Multiple Object Tracking using Flow Linear Programming

Pascal Fua, François Fleuret, Jérôme Berclaz

Multi-object tracking can be achieved by detecting objects in individ- ual frames and then linking detections across frames. Such an approach can be made very robust to the occasional detection failure: If an object is not detected in a frame but is in pre ...

Idiap2009

A Mean Field Approach for Optimization in Particle Systems and Applications

Nicolas Gabriel Gast

This paper investigates the limit behavior of Markov decision processes made of independent particles evolving in a common environment, when the number of particles goes to infinity. In the finite horizon case or with a discounted cost and an infinite hori ...

ICST2009

Matching techniques ride to rescue OLED displays

Combinatorial optimization problems have recently emerged in the design of controllers for OLED displays. The objective is to decompose an image into subframes minimizing the addressing time and thereby also the amplitude of the electrical current through ...

Springer2009

Acoustic sensor network design for position estimation

Volkan Cevher

In this paper, we develop tractable mathematical models and approximate solution algorithms for a class of integer optimization problems with probabilistic and deterministic constraints, with applications to the design of distributed sensor networks that h ...

2009