Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2008.This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.Includes bibliographical references (p. [201]-210).Inference problems, typically posed as the computation of summarizing statistics (e.g., marginals, modes, means, likelihoods), arise in a variety of scientific fields and engineering applications. Probabilistic graphical models provide a scalable framework for developing efficient inference methods, such as message-passing algorithms that exploit the conditional independencies encoded by the given graph. Conceptually, this framework e...
An analytical framework is developed for distributed management of large networks where each node ma...
A current challenge for data management systems is to support the construction and maintenance of ma...
Many inference problems that arise in sensor networks can be formulated as a search for a global exp...
Sensor networks have quickly risen in importance over the last several years to become an active fie...
We study distributed inference, learning and optimization in scenarios which involve networked entit...
Information processing in sensor networks, with many small processors, demands a theory of computati...
Algorithms on graphs are used extensively in many applications and research areas. Such applications...
A promising feature of emerging wireless sensor networks is the opportunity for each spatially-distr...
In this thesis, we consider the problem of decentralized estimation under communication constraints ...
A distributed system is composed of independent agents, machines, processing units, etc., where inte...
The classical framework on distributed inference considers a set of nodes taking measurements and a ...
Central to many statistical inference problems is the computation ofsome quantities defined over var...
Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Mathematics, 2009.Includes bibliogr...
Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Aeronautics and Astronautics, 2010.Ca...
This dissertation deals with developing optimization algorithms which can be distributed over a netw...
An analytical framework is developed for distributed management of large networks where each node ma...
A current challenge for data management systems is to support the construction and maintenance of ma...
Many inference problems that arise in sensor networks can be formulated as a search for a global exp...
Sensor networks have quickly risen in importance over the last several years to become an active fie...
We study distributed inference, learning and optimization in scenarios which involve networked entit...
Information processing in sensor networks, with many small processors, demands a theory of computati...
Algorithms on graphs are used extensively in many applications and research areas. Such applications...
A promising feature of emerging wireless sensor networks is the opportunity for each spatially-distr...
In this thesis, we consider the problem of decentralized estimation under communication constraints ...
A distributed system is composed of independent agents, machines, processing units, etc., where inte...
The classical framework on distributed inference considers a set of nodes taking measurements and a ...
Central to many statistical inference problems is the computation ofsome quantities defined over var...
Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Mathematics, 2009.Includes bibliogr...
Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Aeronautics and Astronautics, 2010.Ca...
This dissertation deals with developing optimization algorithms which can be distributed over a netw...
An analytical framework is developed for distributed management of large networks where each node ma...
A current challenge for data management systems is to support the construction and maintenance of ma...
Many inference problems that arise in sensor networks can be formulated as a search for a global exp...