Particle Filter Rejuvenation and Latent Dirichlet Allocation Chandler May,† Alex Clemmer‡ and Benjamin Van Durme† † Human Language Technology Center of Excellence Johns Hopkins University ‡

Source URL: www.aclweb.org

• Probability and statistics
• Statistics
• Statistical randomness
• Monte Carlo methods
• Stochastic simulation
• Computational statistics
• Sampling techniques
• Statistical mechanics
• Particle filter
• Latent Dirichlet allocation
• Gibbs sampling
• Topic model

Multi-level Monte Carlo for Subsurface Flow

Source URL: www.ifd.mavt.ethz.ch

• Monte Carlo methods
• Porous media
• Statistical randomness
• Stochastic
• Permeability
• Monte Carlo
• Statistics
• Probability
• Applied mathematics

Comparing Least Squares Monte Carlo Methods for Term Structure Option Valuation with Energy Applications Abstract The least squares Monte Carlo (LSM) approach is widely used in financial engineering to value American/Ber

Source URL: wpweb2.tepper.cmu.edu

PCA-enhanced stochastic optimization methods Alina Kuznetsova, Gerard Pons-Moll, and Bodo Rosenhahn⋆ Institute for Information Processing (TNT), Leibniz University Hanover, Germany {kuznetso,pons,rosenhahn}@tnt.uni-han

Source URL: www.tnt.uni-hannover.de

• Statistics
• Applied mathematics
• Numerical analysis
• Metaheuristics
• Computational statistics
• Monte Carlo methods
• Estimation theory
• Statistical mechanics
• Mathematical optimization
• Simulated annealing
• Stochastic optimization
• Gradient descent

Faculty of Science School of Mathematics and Statistics MATH5805 Advanced Monte Carlo Methods

Source URL: www.maths.unsw.edu.au

Monte Carlo Integration ˆ Monte Carlo integration methods are sampling methods, based on probability theory. ˆ They rely on trials to reveal information ˆ From an intuitive point of view, they rest on the central lim

Source URL: ta.twi.tudelft.nl

Discrepancy theory and harmonic analysis Dmitriy Bilyk University of Minnesota “Uniform distribution and quasi-Monte Carlo methods”

Source URL: www.ricam.oeaw.ac.at

Some theoretical aspects of Particle/SMC Methods P. Del Moral INRIA, Centre Bordeaux-Sud Ouest SAMSI Workshop on Sequential Monte Carlo Methods, September 2008.

Source URL: web.maths.unsw.edu.au

Quasi-Newton Methods for Markov Chain Monte Carlo Yichuan Zhang and Charles Sutton School of Informatics University of Edinburgh ,

Source URL: homepages.inf.ed.ac.uk

MCQMCFebruary, 2012 Tenth International Conference on Monte Carlo and Quasi-Monte Carlo Methods in Scientific Computing

Source URL: www.mcqmc2012.unsw.edu.au