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Highly Cited

2008

Highly Cited

2008

Low-rank matrix approximation methods provide one of the simplest and most effective approaches to collaborative filtering. Such… Expand

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Highly Cited

2006

Highly Cited

2006

Differential Evolution (DE) is a simple genetic algorithm for numerical optimization in real parameter spaces. In a statistical… Expand

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Highly Cited

2002

Highly Cited

2002

This paper is about estimating the parameters of the exponential random graph model, also known as the p∗ model, using… Expand

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Highly Cited

2002

Highly Cited

2002

This paper is concerned with simulation-based inference in generalized models of stochastic volatility defined by heavy-tailed… Expand

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Highly Cited

2002

Highly Cited

2002

In a full Bayesian probabilistic framework for "robust" system identification, structural response predictions and performance… Expand

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Highly Cited

1998

Highly Cited

1998

Abstract Markov chain Monte Carlo (MCMC) methods make possible the use of flexible Bayesian models that would otherwise be… Expand

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Highly Cited

1997

Highly Cited

1997

INTRODUCING MARKOV CHAIN MONTE CARLO Introduction The Problem Markov Chain Monte Carlo Implementation Discussion HEPATITIS B: A… Expand

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Highly Cited

1997

Highly Cited

1997

Stochastic simulation Bayesian inference approximate methods of inference Markov chains Gibbs sampling Metropolis-Hastings… Expand

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Highly Cited

1996

Highly Cited

1995