We give the first optimal algorithm for estimating the number of distinct elements in a data
stream, closing a long line of theoretical research on this problem begun by Flajolet and …

We investigate the adversarial robustness of streaming algorithms. In this context, an
algorithm is considered robust if its performance guarantees hold even if the stream is …

We study the ℓ1-low rank approximation problem, where for a given nxd matrix A and
approximation factor α≤ 1, the goal is to output a rank-k matrix  for which‖ A-Â‖ 1≤ α …

In this paper, we present near-optimal space bounds for Lp-samplers. Given a stream of
updates (additions and subtraction) to the coordinates of an underlying vector x in Rn, a …

In the adversarially robust streaming model, a stream of elements is presented to an
algorithm and is allowed to depend on the output of the algorithm at earlier times during the …

We consider the following k-sparse recovery problem: design an m× n matrix A, such that for
any signal x, given Ax we can efficiently recover○ satisfying‖ x–○‖ 1≤ C min k-sparse …

We prove an optimal Ω (n) lower bound on the randomized communication complexity of the
much-studied Gap-Hamming-Distance problem. As a consequence, we obtain essentially …

This paper introduces arithmetic sketching, an abstraction of a primitive that several previous
works use to achieve lightweight, low-communication zero-knowledge verification of secret …

The streaming model of computation is a popular approach for working with large-scale
data. In this setting, there is a stream of items and the goal is to compute the desired …

We study the Kronecker product regression problem, in which the design matrix is a
Kronecker product of two or more matrices. Formally, given $ A_i\in\R^{n_i\times d_i} $ for …