Concept

Monte Carlo algorithm

Related publications (46)

On the benefits of vector network coding

Christina Fragouli, Javad Ebrahimi Boroojeni

In vector network coding, the source multi- casts information by transmitting vectors of length L, while intermediate nodes process and combine their incoming packets by multiplying them with L × L coding matrices that play a similar role as coding coeffic ...

2010

Approximate Confidence Computation in Probabilistic Databases.

Christoph Koch

This paper introduces a deterministic approximation algorithm with error guarantees for computing the probability of propositional formulas over discrete random variables. The algorithm is based on an incremental compilation of formulas into decision diagr ...

2010

Hybrid Numerical Solution of the Chemical Master Equation

Maria-Emanuela-Canini Mateescu, Verena Wolf

We present a numerical approximation technique for the analysis of continuous-time Markov chains that describe networks of biochemical reactions and play an important role in the stochastic modeling of biological systems. Our approach is based on the const ...

2010

Connected facility location via random facility sampling and core detouring

Friedrich Eisenbrand, Thomas Rothvoss

We present a simple randomized algorithmic framework for connected facility location problems. The basic idea is as follows: We run a black-box approximation algorithm for the unconnected facility location problem, randomly sample the clients, and open the ...

2010

A branch and bound algorithm for disassembly scheduling with assembly product structure⋆

Paul Xirouchakis, Hwa-Joong Kim

This paper considers a production planning problem in disassembly systems, which is the problem of determining the quantity and timing of disassembling end-of-use/life products in order to satisfy the demand of their parts or components over a planning hor ...

2009

Complexity of stochastic branch and bound methods for belief tree search in Bayesian reinforcement learning

Christos Dimitrakakis

There has been a lot of recent work on Bayesian methods for reinforcement learning exhibiting near-optimal online performance. The main obstacle facing such methods is that in most problems of interest, the optimal solution involves planning in an infinite ...

2009

COMPLEXITY OF STOCHASTIC BRANCH AND BOUND METHODS FOR BELIEF TREE SEARCH IN BAYESIAN REINFORCEMENT LEARNING

Christos Dimitrakakis

2009

On the Complexity of Asynchronous Gossip

Rachid Guerraoui, Seth Gilbert

In this paper, we study the complexity of gossip in an asynchronous, message-passing fault-prone distributed system. In short, we show that an adaptive adversary can significantly hamper the spreading of a rumor, while an oblivious adversary cannot. In the ...

2008

Approximating connected facility location problems via Random facility sampling and core detouring

Friedrich Eisenbrand, Thomas Rothvoss

2008

A tutorial on adaptive MCMC

Johannes Thoms

We review adaptive Markov chain Monte Carlo algorithms (MCMC) as a mean to optimise their performance. Using simple toy examples we review their theoretical underpinnings, and in particular show why adaptive MCMC algorithms might fail when some fundamental ...

2008

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.