Ciamac C. Moallemi: Research and Publications

I am broadly interested in the intersection of probability and optimization theory, and in particular in the optimization and control of large-scale stochastic systems. Research problems that I have considered in this setting are typically distinguished one of several features. First, the large size of problem instances precludes exact solution and requires approximation methods. Second, such systems are often naturally distributed, and hence decentralized methods of solution and distributed control policies are particularly important. Finally, explicit probabilistic models for aspects of the system dynamics are often unavailable, thus methods which can learn from historical data or from online system trajectories are relevant.

Specific methodologies include approximate dynamic programming, message-passing algorithms, and machine learning; and application areas include service and communications networks, e-commerce, data-mining, and financial engineering.

Short research briefs that feature some of my work are available here:

Publications by Year

Publications by Topic

2010

[19]

M. Broadie, Y. Du, C. C. Moallemi. Efficient risk estimation via nested sequential simulation. Working paper. Initial version: February 2010.
[pdf]

[18]

K. Iyer, R. Johari, C. C. Moallemi. Information aggregation and allocative efficiency in smooth markets. Working paper. Initial version: January 2010. Revised: July 2010.
[pdf]

Preliminary version:

K. Iyer, R. Johari, C. C. Moallemi. Information aggregation in smooth markets. In EC '10: Proceedings of the 11th ACM conference on Electronic Commerce, pp. 199–206, June 2010.
[doi]

2009

[17]

C. C. Moallemi, M. Sağlam. The cost of latency. Working paper. Initial version: November 2009. Revised: June 2010.
[pdf]

[16]

C. C. Moallemi, D. Shah. On the flow-level dynamics of a packet-switched network. Working paper. Initial version: November 2009. Revised: February 2010.
[pdf]

Preliminary version:

C. C. Moallemi, D. Shah. On the flow-level dynamics of a packet-switched network. In SIGMETRICS '10: Proceedings of the ACM SIGMETRICS international conference on Measurement and modeling of computer systems, pp. 83–94, June 2010.
[doi]

[15]

V. V. Desai, V. F. Farias, C. C. Moallemi. Approximate dynamic programming via a smoothed linear program. Working paper. Initial version: August 2009. Revised: July 2010.
[pdf]

Preliminary version:

V. V. Desai, V. F. Farias, C. C. Moallemi. A smoothed approximate linear program. In Advances in Neural Information Processing Systems 22, pp. 459–467, 2009.

2008

[14]

C. C. Moallemi, B. Park, B. Van Roy. Strategic execution in the presence of an uninformed arbitrageur. Working paper. Initial version: January 2008. Revised: February 2010.
[pdf]

2007

[13]

C. C. Moallemi. A Message-Passing Paradigm for Optimization. Ph.D. thesis, Stanford University, September 2007.
[pdf]

[12]

V. F. Farias, C. C. Moallemi, B. Van Roy, T. Weissman. Universal reinforcement learning. IEEE Transactions on Information Theory, 56(5):2441–2454, May 2010.
[pdf] [doi]

Preliminary version:

V. F. Farias, C. C. Moallemi, B. Van Roy, T. Weissman. A universal scheme for learning. In Proceedings of the IEEE International Symposium on Information Theory, pp. 1158–1162, Adelaide, Australia, September 2005.
[doi]

[11]

C. C. Moallemi, B. Van Roy. Resource allocation via message passing. To appear in INFORMS Journal of Computing. Initial version: June 2007. Revised: March 2010.
[pdf] [online supplement]

[10]

C. C. Moallemi, B. Van Roy. Convergence of min-sum message passing for convex optimization. IEEE Transactions on Information Theory, 56(4):2041–2050, April 2010.
[pdf] [doi]

Preliminary version:

C. C. Moallemi, B. Van Roy. Convergence of the min-sum algorithm for convex optimization. In Proceedings of the 45th Allerton Conference on Communication, Control and Computing, Monticello, IL, September 2007.

2006

[9]

C. C. Moallemi, B. Van Roy. Convergence of min-sum message passing for quadratic optimization. IEEE Transactions on Information Theory, 55(5):2413–2423, May 2009.
[pdf] [doi]

[8]

C. C. Moallemi, S. Kumar, B. Van Roy. Approximate and data-driven dynamic programming for queueing networks. Working paper. Initial version: December 2006. Revised: September 2008.
[pdf]

2005

[7]

V. F. Farias, C. C. Moallemi, B. Prabhakar. Load balancing with migration penalties. In Proceedings of the IEEE International Symposium on Information Theory, pp. 558–562, Adelaide, Australia, September 2005.
[pdf] [doi]

[6]

C. C. Moallemi, B. Van Roy. Consensus propagation. IEEE Transactions on Information Theory, 52(11):4753–4766, November 2006.
[pdf] [doi]

Preliminary version:

C. C. Moallemi, B. Van Roy. Consensus propagation. In Advances in Neural Information Processing Systems 18, MIT Press, pp. 899–906, 2006.

2003

[5]

J. M. Johnson, K. Mason, C. C. Moallemi, H. Xi, S. Somaroo, E. Huang. Protein family annotation in a multiple alignment viewer. Bioinformatics, 19(4):544–545, 2003.
[doi]

[4]

C. C. Moallemi, B. Van Roy. Distributed optimization in adaptive networks. In Advances in Neural Information Processing Systems 16, MIT Press, 2004.
[pdf] [appendix]

Preliminary version:

C. C. Moallemi, B. Van Roy. Decentralized protocols for optimization of sensor networks. In Proceedings of the 42nd Allerton Conference on Communication, Control and Computing, Monticello, IL, September 2003.

[3]

K. Mason, N. M. Patel, A. Ledell, C. C. Moallemi, E. A. Wintner. Mapping protein pockets through their potential small-molecule binding volumes: QSCD applied to biological protein structures. Journal of Computer-Aided Molecular Design, 18(1):55–70, 2004.
[doi]

2000

[2]

E. A. Wintner, C. C. Moallemi. Quantized Surface Complementarity Diversity (QSCD): A model based on small molecule-target complementarity. Journal of Medicinal Chemistry, 43(10):1993–2006, 2000.
[doi]

1991

[1]

C. C. Moallemi. Neural networks in the computer analysis of voided urine cells for bladder cancer. IEEE Expert, 6(6):8–12, December 1991.
[doi]