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Estimation of discrete choice models with hybrid stochastic adaptive batch size algorithms

Publications associées (101)

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An Algorithm for Testing the Efficient Market Hypothesis

Ioana Andreea Boboc

The objective of this research is to examine the efficiency of EUR/USD market through the application of a trading system. The system uses a genetic algorithm based on technical analysis indicators such as Exponential Moving Average (EMA), Moving Average C ...

Public Library of Science2013

A survey and comparison of contemporary algorithms for computing the matrix geometric mean

In this paper we present a survey of various algorithms for computing matrix geometric means and derive new second-order optimization algorithms to compute the Karcher mean. These new algorithms are constructed using the standard definition of the Riemanni ...

2012

Coordination and Sampling in Distributed Constraint Optimization

Brammert Ottens

The Distributed Constraint Optimization (DCOP) framework can be used to model a wide range of optimization problems that are inherently distributed. A distributed optimization problem can be viewed as a problem distributed over a set of agents, where agent ...

EPFL2012

Fast algorithm for blind optimization of optical systems. Statistics and methodology

Maria-Alexandra Paun

Adaptive Optics (AO) improves the efficiency of the optical devices in confocal imaging systems by reducing wavefront aberrations. Aberration is caused by imperfections within the system and reduces the optical signal to noise ratio of the resultant images ...

Natl Inst Optoelectronics2012

Synthesis of sparse arrays with focused or shaped beampattern via sequential convex optimizations

Benjamin Fuchs

An iterative procedure for the synthesis of sparse arrays radiating focused or shaped beampattern is presented. The algorithm consists in solving a sequence of weighted l(1) convex optimization problems. The method can thus be readily implemented and effic ...

Institute of Electrical and Electronics Engineers2012

Unsupervised algorithms for distributed estimation over adaptive networks

Ali H. Sayed

This work shows how to develop distributed versions of block blind estimation techniques that have been proposed before for batch processing. Using diffusion adaptation techniques, data are accumulated at the nodes to form estimates of the auto-correlation ...

IEEE2012

Ultra-Fast Optimization Algorithm for Sparse Multi Kernel Learning

Jie Luo

Many state-of-the-art approaches for Multi Kernel Learning (MKL) struggle at finding a compromise between performance, sparsity of the solution and speed of the optimization process. In this paper we look at the MKL problem at the same time from a learning ...

2011

Ultra-Fast Optimization Algorithm for Sparse Multi Kernel Learning

Jie Luo

Idiap2011

Container Terminal Management

Ilaria Vacca

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 ...

EPFL2011

Hybrid Simulated Annealing and Its Application to Optimization of Hidden Markov Models for Visual Speech Recognition

Jong Seok Lee

We propose a novel stochastic optimization algorithm, hybrid simulated annealing (SA), to train hidden Markov models (HMMs) for visual speech recognition. In our algorithm, SA is combined with a local optimization operator that substitutes a better solutio ...

2010