We consider a network of agents that must solve an online optimization problem from
continual observation of streaming data. To this end, the agents implement a distributed …

Wu and Verdú developed a theory of almost lossless analog compression, where one
imposes various regularity conditions on the compressor and the decompressor with the …

Abstract Let X⊂ RN be a Borel set, μ a Borel probability measure on X and T: X→ X a locally
Lipschitz and injective map. Fix k∈ N strictly greater than the (Hausdorff) dimension of X and …

In this work we derive the performance achievable by a network of distributed agents that
solve, adaptively and in the presence of communication constraints, a regression problem …

We propose an information-theoretic framework for analog signal separation. Specifically,
we consider the problem of recovering two analog signals, modeled as general random …

In a previous work we proved that if a finite Borel measure $\mu $ in a Euclidean space has
Hausdorff dimension smaller than a positive integer $ k $, then the orthogonal projection …

We propose a theory for matrix completion that goes beyond the low-rank structure
commonly considered in the literature and applies to general matrices of low description …

R\'enyi Information Dimension (RID) plays a central role in quantifying the compressibility of
random variables with singularities in their distribution, encompassing and extending …

In this paper, we study the lossless analog compression for iid nonsingular signals. Through
analyzing analog polarization under Hadamard transform, we propose efficient successive …

This paper is concerned with the lossy compression of general random variables,
specifically with rate-distortion theory and quantization of random variables taking values in …