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Meeting Activities

** Clicking on a date will take you to that date on the Meeting Summary page **

DATE	TOPICS & Readings	Notes
5/6/09	Jim Lynch discussed the connection between his current work [14], and the topics we discussed the past few weeks .
4/29/09	Jim Lynch continued his discussion of papers [10], and [11], .	See his Slides
4/15/09	Jim Lynch discussed papers [10], and [11], .	See his Slides
4/1/09	Jim Lynch discussed the results covered in the paper he recently submitted with his student Shuang Li [9], .
2/18/09	Jim Lynch will continue his talk from last week and discuss possible applications of SMC.
2/12/09	Jim Lynch will be giving a talk titled "On the Markovian Structure for Complex Monotone Load-Sharing Systems" based on joint work with his student Shuang Li. To prepare for the meeting, please see his current draft, On a Gibbs Measure/Markov Random Field Representation for Complex Load-Sharing Systems, posted under Reference Matericals on the Secure Website.	Jim's Presentation Slides
11/12/08	Mark Huber suggested some potential projects for subgroups, based on readings from previous weeks. .	See his Slides.
11/05/08	Mark Huber discussed the papers by Eberle and Marinelli , [8] .	See his Slides.
10/29/08	Mark Huber introduced parallel and simulated tempering.	See his Slides.
10/22/08	Mark Huber discusses the content of [5].	See his Slides.
10/15/08	Mark Huber talks about the Product Estimator with applications to the Ising model and finding the volume of a convex body.	See his Slides.
10/08/08	Mark Huber will review the Randomness Recycler and begin to discuss convergence.	See his Slides.
10/01/08	Mark Huber talks about the Randomness Recycler. Read [1], [2], [3] in preparation.	See his Slides.

Group Members

(group email alias is smc-theory at samsi.info)

Name	Affiliation	Email Address
Petar Djuric	Stony Brook University	djuric AT ece DOT sunysb DOT edu
Simon Godsill	University of Cambridge	sjg AT eng DOT cam DOT ac DOT uk
Jan Hannig	UNC-Chapel Hill	hannig AT email DOT unc DOT edu
Mark Huber	Duke University	mhuber AT math DOT duke DOT edu
Jim Lynch	University of South Carolina	lynch AT stat DOT sc DOT edu
Jonathan Mattingly	Duke University	jonm AT math DOT duke DOT edu
Edsel Pena	University of South Carolina	pena AT stat DOT sc DOT edu
Gareth Peters		peterga AT maths DOT unsw DOT edu DOT au
Giovanni Petris	University of Arkansas	GPetris AT uark DOT edu
Clyde Schoolfield	University of Florida	clyde AT stat DOT ufl DOT edu
Sarah Schott	Duke University	schott AT math DOT duke DOT edu
Namrata Vaswani	Iowa State University	namrata AT iastate DOT edu
Anand Vidyashankar	Cornell University	anv4 AT cornell DOT edu
Robert L Wolpert	Duke University	wolpert AT stat DOT duke DOT edu

Reference List

(bibliographic format)

1. J. A. Fill and M. L Huber, The Randomness Recycler: A New Approach to Perfect Simulation
2. J. A. Fill and M. L. Huber,The Randomness Recycler: A New Technique for Perfect Sampling, Proc. of the 41th Annual IEEE Symposium on the Foundations of Computer Science (2000)
3. J. A. Fill and M. L. Huber,The Randomness Recycler Approach to Perfect Sampling, 53rd annual meeting of the ISI (2001)
4. J. D. Lynch and J. Sethuraman, On the Ergodicity of General State Space Markov Chains
5. D. Stefankovic, S. Vempala, E. Vigoda Adaptive Simulated Annealing: A Near-optimal Connection between Sampling and Counting, arXiv:cs/0612058v1 [cs.DS], (2006)
6. A. Eberle and C. Marinelli, Lp Estimates for Feynman-Kac Propagators, (2008)
7. A. Eberle and C. Marinelli, Quantitative Approximations of Evolving Probability Measures and Sequential Markov Chain Monte Carlo Methods (2008)
8. A. Eberle and C. Marinelli, Convergence os Sequential Markov Chain Monte Carlo Methods: I. Nonlinear Flow of Probability Measures arXiv:math/0612074v1 [math.PR], (2006)
9. S. Li and J. Lynch, On a Gibbs Measure Representation for Complex Load-Sharing Parallel Systems Applied Probability Trust
10. J. Moller, A. N. Pettit, R. Reeves, and K. K. Berthelsen An efficient Markov chain Monte Carlo method for distributions with intractable normalising constants Biometrika(2006), 93, 2, pp.451-458
11. I. Murray, Z. Ghahramani, and D. MacKay MCMC for doubly-intractable distributions
12. R. Neal Estimating Rations of Normalizing Constants Using Linked Importance Sampling
13. R. Neal Taking Bigger Metropolis Steps by Dragging Fast Variables
14. D. Banks, G. Datta, A. Karr, J. Lynch, J. Niemi, and F. Vera Bayesian CAR Models for Syndromic Surveillance on Multiple Data Streams: Theory and Practice

Data Sites

Working Groups Dial-in & WebEx Instructions

1. Go to the email invitation that you received announcing the meeting, or go directly to WebEx: https://samsi.webex.com
2. Click on the link for the meeting you want to join
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Theory Working Group

Meets: Wednesday, 10:15-12:00 in NISS Room 104

Leader: Mark Huber
Webmaster: Sarah Schott

Meeting Activities

Group Members

Reference List

Data Sites

Theory Working Group

Meets: Wednesday, 10:15-12:00 in NISS Room 104 Leader: Mark Huber Webmaster: Sarah Schott

Meeting Activities

Group Members

Reference List

Data Sites

Meets: Wednesday, 10:15-12:00 in NISS Room 104

Leader: Mark Huber
Webmaster: Sarah Schott