The frequent items problem is to process a stream of items and find all items occurring more than a given fraction of the time. It is one of the most heavily studied problems in d...
—Subspaces offer convenient means of representing information in many pattern recognition, machine vision, and statistical learning applications. Contrary to the growing populari...
The (decisional) learning with errors problem (LWE) asks to distinguish “noisy” inner products of a secret vector with random vectors from uniform. In recent years, the LWE pro...
This paper considers the problem of completing a matrix with many missing entries under the assumption that the columns of the matrix belong to a union of multiple low-rank subspa...
Abstract— Flooding based strategies are conventionally employed to perform querying and broadcasting in sensor networks. These schemes have low hop-delays of Θ( 1 M(n) ) to reac...
Sundar Subramanian, Sanjay Shakkottai, Ari Arapost...