We study the following one-way asymmetric transmission problem, also a variant of model-
based compressed sensing: a resource-limited encoder has to report a small set $ S $ from …

We revisit the problem of Compression under Uncertain Priors: the sender knows a
distribution P over [N] and the receiver knows a distribution Q over [N] such that P, Q are∆ …

We consider the problem of recovering a sparse vector from a quantized or a lossy
compressed version of its noisy random linear projections. We characterize the minimal …

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 …

The zero-error channel capacity is the maximum asymptotic rate that can be reached with
error probability exactly zero, instead of a vanishing error probability. The nature of this …

Compressed Sensing is mostly known for finding exact or approximate solutions for
underdetermined linear systems of equations, which could not be solved using traditional …

The emerging paradigm of ubiquitous low-cost sensors with wireless connectivity and data
processing in the cloud promises to be an enabling technology for applications such as …

The existence of significant amount of correlation in the network traffic has stimulated the
development of innetwork traffic reduction techniques since end-to-end universal …

This article describes a very different approach to the decentralized compression of
networked data. Considering a particularly salient aspect of this struggle that revolves …