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- Ciamac C. Moallemi, Benjamin Van Roy
- IEEE Transactions on Information Theory
- 2005

We propose consensus propagation, an asynchronous distributed protocol for averaging numbers across a network. We establish convergence, characterize the convergence rate for regular graphs, and demonstrate that the protocol exhibits better scaling properties than pairwise averaging, an alternative that has received much recent attention. Consensus… (More)

- Vijay V. Desai, Vivek F. Farias, Ciamac C. Moallemi
- Operations Research
- 2012

We present a novel linear program for the approximation of the dynamic programming costto-go function in high-dimensional stochastic control problems. LP approaches to approximate DP have typically relied on a natural ‘projection’ of a well studied linear program for exact dynamic programming. Such programs restrict attention to approximations that are… (More)

- Vijay V. Desai, Vivek F. Farias, Ciamac C. Moallemi
- Management Science
- 2012

We introduce the pathwise optimization (PO) method, a new convex optimization procedure to produce upper and lower bounds on the optimal value (the ‘price’) of a high-dimensional optimal stopping problem. The PO method builds on a dual characterization of optimal stopping problems as optimization problems over the space of martingales, which we dub the… (More)

- Ciamac C. Moallemi, Benjamin Van Roy
- IEEE Transactions on Information Theory
- 2009

We establish the convergence of the min-sum message passing algorithm for minimization of a quadratic objective function given a convex decomposition. Our results also apply to the equivalent problem of the convergence of Gaussian belief propagation.

- Vijay V. Desai, Vivek F. Farias, Ciamac C. Moallemi
- NIPS
- 2009

We present a novel linear program for the approximation of the dynamic programming cost-to-go function in high-dimensional stochastic control problems. LP approaches to approximate DP naturally restrict attention to approximations that are lower bounds to the optimal cost-to-go function. Our program – the ‘smoothed approximate linear program’ – relaxes this… (More)

We establish that the min-sum message-passing algorithm and its asynchronous variants converge for a large class of unconstrained convex optimization problems.

- Mark Broadie, Yiping Du, Ciamac C. Moallemi
- Management Science
- 2011

W analyze the computational problem of estimating financial risk in a nested simulation. In this approach, an outer simulation is used to generate financial scenarios, and an inner simulation is used to estimate future portfolio values in each scenario. We focus on one risk measure, the probability of a large loss, and we propose a new algorithm to estimate… (More)

We present a novel linear program for the approximation of the dynamic programming costto-go function in high-dimensional stochastic control problems. LP approaches to approximate DP have typically relied on a natural ‘projection’ of a well studied linear program for exact dynamic programming. Such programs restrict attention to approximations that are… (More)

- Jason M. Johnson, Keith Mason, Ciamac C. Moallemi, Hualin Xi, Shyamal Somaroo, Enoch S. Huang
- Bioinformatics
- 2003

SUMMARY
The Pfaat protein family alignment annotation tool is a Java-based multiple sequence alignment editor and viewer designed for protein family analysis. The application merges display features such as dendrograms, secondary and tertiary protein structure with SRS retrieval, subgroup comparison, and extensive user-annotation capabilities.
… (More)

- Ciamac C. Moallemi, Benjamin Van Roy
- IEEE Transactions on Information Theory
- 2010

We establish that the min-sum message-passing algorithm and its asynchronous variants converge for a large class of unconstrained convex optimization problems, generalizing existing results for pairwise quadratic optimization problems. The main sufficient condition is that of scaled diagonal dominance. This condition is similar to known sufficient… (More)