We give the first polynomial time algorithm to learn any function of a constant number of halfspaces under the uniform distribution on the Boolean hypercube to within any constan...
We propose a new framework for discussing computational complexity of problems involving uncountably many objects, such as real numbers, sets and functions, that can be represente...
We propose PASTE, the first differentially private aggregation algorithms for distributed time-series data that offer good practical utility without any trusted server. PASTE add...
Estimating the number of distinct values is a wellstudied problem, due to its frequent occurrence in queries and its importance in selecting good query plans. Previous work has sh...
We propose an novel method of computing and storing DataCubes. Our idea is to use Bayesian Networks, which can generate approximate counts for any query combination of attribute v...