An Information-Based Approximation Scheme for Stochastic Optimization Problems in Continuous Time
Graph Chatbot
Chat with Graph Search
Ask any question about EPFL courses, lectures, exercises, research, news, etc. or try the example questions below.
DISCLAIMER: The Graph Chatbot is not programmed to provide explicit or categorical answers to your questions. Rather, it transforms your questions into API requests that are distributed across the various IT services officially administered by EPFL. Its purpose is solely to collect and recommend relevant references to content that you can explore to help you answer your questions.
This thesis deals with models and methods for large scale optimization problems; in particular, we focus on decision problems arising in the context of seaport container terminals for the efficient management of terminal operations. Large-scale optimizatio ...
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 ...
Stochastic programming and robust optimization are disciplines concerned with optimal decision-making under uncertainty over time. Traditional models and solution algorithms have been tailored to problems where the order in which the uncertainties unfold i ...
The process industries are characterized by a large number of continuously operating plants, for which optimal operation is of economic importance. However, optimal operation is particularly difficult to achieve when the process model used in the optimizat ...
Linear stochastic programming provides a flexible toolbox for analyzing real-life decision situations, but it can become computationally cumbersome when recourse decisions are involved. The latter are usually modeled as decision rules, i.e., functions of t ...
We consider the problem of distributed classification of multiple observations of the same object that are collected in an ad hoc network of vision sensors. Assuming that each sensor captures a different observation of the same object, the problem is to cl ...
Institute of Electrical and Electronics Engineers2011
Within the HMM state mapping-based cross-lingual speaker adaptation framework, the minimum Kullback-Leibler divergence criterion has been typically employed to measure the similarity of two average voice state distributions from two respective languages fo ...
Within the HMM state mapping-based cross-lingual speaker adaptation framework, the minimum Kullback-Leibler divergence criterion has been typically employed to measure the similarity of two average voice state distributions from two respective languages fo ...
We present ABC, a software tool for automatically computing symbolic upper bounds on the number of iterations of nested program loops. The system combines static analysis of programs with symbolic summation techniques to derive loop invariant relations bet ...
This article describes a bounding approximation scheme for convex multistage stochastic programs (MSP) that constrain the conditional expectation of some decision-dependent random variables. Expected value constraints of this type are useful for modelling ...
