Jack H. Lutz

If $S$ is an infinite sequence over a finite alphabet $\Sigma$ and $\beta$ is a probability measure on $\Sigma$, then the {\it dimension} of $ S$ with respect to $\beta$, written $\dim^\beta(S)$, is a constructive version of Billingsley dimension that coincides with the (constructive Hausdorff) dimension $\dim(S)$ when $\beta$ is ... more >>>

Gillat Kol, Ran Raz

We study the interactive channel capacity of an $\epsilon$-noisy channel. The interactive channel capacity $C(\epsilon)$ is defined as the minimal ratio between the communication complexity of a problem (over a non-noisy channel), and the communication complexity of the same problem over the binary symmetric channel with noise rate $\epsilon$, where ... more >>>

Louay Bazzi

A classical bound in Information Theory asserts that small $L_1$-distance between probability distributions implies small difference in Shannon entropy, but the converse need not be true. We show that if a probability distribution on $\{0,1\}^n$ has small-bias, then the converse holds for its weight distribution in the proximity of the ... more >>>

Tom Gur, Min-Hsiu Hsieh, Sathyawageeswar Subramanian

Entropy is a fundamental property of both classical and quantum systems, spanning myriad theoretical and practical applications in physics and computer science. We study the problem of obtaining estimates to within a multiplicative factor $\gamma>1$ of the Shannon entropy of probability distributions and the von Neumann entropy of mixed quantum ... more >>>