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Project Highlight: Approximate Dynamic Programming Using Bellman Residual Elimination

Markov Decision Processes (MDPs) are a powerful and general framework for addressing problems involving sequential decision-making under uncertainty.  Such problems occur ...

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Project Highlight: Classification and Dimensionality Reduction Using Geometric Level Set Methods

Shell International uses noisy measurements to tell the difference between two types of rock, sandstone and shale, which is useful for ...

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Project Highlight: Communication and Learning in Social Networks

Most individuals form their opinions about the quality of products, social trends and political issues via their interactions in social and economic ...

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Project Highlight: Large-Deviation Analysis for the Learning of Markov Tree Structures

Learning the structure of a graphical model (or Bayesian network) from data is a fundamental task in many scientific domains. In this work, ...

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Project Highlight: Sum of Squares and Polynomial Convexity

Given a multivariate polynomial how can we decide if it is globally nonnegative? This basic question appears ubiquitously in various areas ...

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Project Highlight: Non-monotonic Lyapunov Functions for Analysis of Nonlinear Systems

Lyapunov’s stability theorem and its many variants comprise a central core of control theory and have a wide array of applications ranging from ...

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Project Highlight: Market Mechanisms for Matching Supply and Demand in Smart Power Grids

In the transformation of today’s power grids to smart grids, a major challenge to be overcome is to offset the supply-side ...

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Project Highlight: Scaling Laws for Heterogeneous Wireless Networks

We develop approximate asymptotic characterizations of the performance of large heterogeneous wireless networks. We consider the impact of location, traffic, and service heterogeneity. ...

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Project Highlight: Influence of a Degraded Environment on Airspace Safety

The current air transportation system (ATS) is being pushed to operate ever closer to its critical capacity, leading to increases in both the ...

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Project Highlight: Finding the Culprit

In many scenarios such as the spread of viruses in computer networks, the spread of (mis)information in social networks and even the spread ...

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Project Highlight: Decentralized Spacecraft Formation Flight

The objective of this research is the development of control mechanisms for spacecraft formation flight with minimal information transfer between spacecraft. The ...

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December 2013: LIDS Director Alan Willsky wins 2013 SPS Society Award

LIDS Director Alan Willsky has been distinguished as the winner of the 2013 SPS Society Award of the IEEE Signal Processing Society (SPS).

The SPS Society Award is the highest award bestowed by the IEEE Signal Processing Society, and honors outstanding technical contributions in a field within its scope and outstanding leadership in that field. The award citation reads: "For fundamental contributions to probabilistic modeling and for pioneering work in the development and application of multi-resolution statistical methods."

November 2013: MIT News office article on Willsky and Liu

Ying Liu and Alan Willsky's work on probabilistic graphical models and feedback vertex sets is featured in an article from the MIT News office.

October 2013: LIDS Alum Jagdish Ramakrishnan finalist for INFORMS Dantzig Dissertation Prize

Recent LIDS alum, Jagdish Ramakrishnan, was selected as a finalist for the INFORMS George B. Dantzig Dissertation Prize, for his thesis on "Dynamic Optimization of Fractionation Schedules in Radiation Therapy," co-supervised by Drs. Bortfeld and Craft (from MGH) and Tsitsiklis (from LIDS).

The George B. Dantzig Award is given for the best dissertation in any area of operations research and the management sciences that is innovative and relevant to practice.

October 2013: Prof. Devavrat Shah and Jinwoo Shin receive INFORMS 2013 Best Publication Award

The Applied Probability Society of INFORMS presents its 2013 Best Publication Award to Devavrat Shah and Jinwoo Shin for their paper, "Randomized Scheduling Algorithm for Queuing Networks".

The Award recognizes an outstanding contribution to the field of Applied Probability during the years 2010-2013.


LIDS Seminar
May 13, 2014, 4pm, 32-155
Michael J. Neely (University of Southern California)
Distributed Stochastic Optimization via Correlated Scheduling