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—This paper studies optimization of zero-delay source-channel codes, and specifically the problem of obtaining globally optimal transformations that map between the source space and the channel space, under a given transmission power constraint and for the mean square error distortion. Particularly, we focus on the setting where the decoder has access to… (More)

— " To be considered for an IEEE Jack Keil Wolf ISIT Student Paper Award. " This paper proposes an optimization method, based on information theoretic ideas, to a class of distributed control problems. As a particular test case, the well-known and numerically " over-mined " problem of decentralized control and implicit communication, commonly referred to as… (More)

This paper studies the optimization of zero-delay analog mappings in a network setting that involves distributed coding. The cost surface is known to be non-convex, and known greedy methods tend to get trapped in poor locally optimal solutions that depend heavily on initialization. We derive an optimization algorithm based on the principles of "… (More)

—This paper studies the problem of global optimization of zero-delay source-channel codes that map between the source space and the channel space, under a given transmission power constraint and for the mean square error distortion. Particularly, we focus on two well known network settings: the Wyner-Ziv setting where only a decoder has access to side… (More)

This paper extends the well-known source coding problem of multiple descriptions, in its general and basic setting, to analog source-channel coding scenarios. Encoding-decoding functions that optimally map between the (possibly continuous valued) source and the channel spaces are numerically derived. The main technical tool is a non-convex optimization… (More)

—This note studies the global optimization of controller mappings in discrete-time stochastic control problems including Witsenhausen's celebrated 1968 counterexample. We propose a generally applicable non-convex numerical optimization method based on the concept of deterministic annealing – which is derived from information theoretic principles and was… (More)

— This paper studies the problem of mapping optimization in decentralized control problems. A global optimization algorithm is proposed based on the ideas of " deterministic annealing "-a powerful non-convex optimization framework derived from information theoretic principles with analogies to statistical physics. The key idea is to randomize the map-pings… (More)

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