We consider the problem of one-way communication when the recipient does not know exactly the distribution that the messages are drawn from, but has a “prior ” distribution that is known to be close to the source distribution, a problem first considered by Juba et al. [5]. This problem generalizes the classical source coding problem in information theory, in which the receiver knows the source distribution exactly, that was first considered in Shannon’s work [6]. This “uncertain priors ” coding problem was intended to illuminate aspects of natural language communication, and has applications to adaptive compression schemes. We consider the question of how much longer the messages need to be in order to cope with the uncertainty that the sen...
In the first chapter, two general classes of optimization problems are discussed. The application of...
Error correction and message authentication are well studied in the literature, and various efficien...
We consider a worst-case asymmetric distributed source coding problem where an information sink comm...
Communication in “natural ” settings, e.g., between humans, is distinctly different than that in cla...
We introduce a simple model illustrating the utility of context in compressing communication and the...
Compression is a fundamental goal of both human language and digital communication, yet natural lang...
Data compression is a fundamental problem in quantum and classical information theory. A typical ver...
The transmission of information over a communication channel vastly depends on the level of knowledg...
In a recent work (Ghazi et al., SODA 2016), the authors with Komargodski and Kothari initiated the s...
In this paper we analyze a cheap-talk model with a partially informed receiver. In clear contrast to...
We consider an information design problem when the sender faces ambiguity regarding the probability ...
(to appear)International audienceThis paper investigates a multi-terminal source coding problem unde...
Thesis: Ph. D., Massachusetts Institute of Technology, Department of Electrical Engineering and Comp...
This thesis studies several problems in information theory where the notion of causality comes into ...
Shannon’s channel coding theorem characterizes the maximal rate of information that can be reliably ...
In the first chapter, two general classes of optimization problems are discussed. The application of...
Error correction and message authentication are well studied in the literature, and various efficien...
We consider a worst-case asymmetric distributed source coding problem where an information sink comm...
Communication in “natural ” settings, e.g., between humans, is distinctly different than that in cla...
We introduce a simple model illustrating the utility of context in compressing communication and the...
Compression is a fundamental goal of both human language and digital communication, yet natural lang...
Data compression is a fundamental problem in quantum and classical information theory. A typical ver...
The transmission of information over a communication channel vastly depends on the level of knowledg...
In a recent work (Ghazi et al., SODA 2016), the authors with Komargodski and Kothari initiated the s...
In this paper we analyze a cheap-talk model with a partially informed receiver. In clear contrast to...
We consider an information design problem when the sender faces ambiguity regarding the probability ...
(to appear)International audienceThis paper investigates a multi-terminal source coding problem unde...
Thesis: Ph. D., Massachusetts Institute of Technology, Department of Electrical Engineering and Comp...
This thesis studies several problems in information theory where the notion of causality comes into ...
Shannon’s channel coding theorem characterizes the maximal rate of information that can be reliably ...
In the first chapter, two general classes of optimization problems are discussed. The application of...
Error correction and message authentication are well studied in the literature, and various efficien...
We consider a worst-case asymmetric distributed source coding problem where an information sink comm...