We propose a new unsupervised learning technique for extracting information from large text collections. We model documents as if they were generated by a two-stage stochastic pro...
Mark Steyvers, Padhraic Smyth, Michal Rosen-Zvi, T...
High-dimensional collections of 0-1 data occur in many applications. The attributes in such data sets are typically considered to be unordered. However, in many cases there is a n...
In the past, Field Programmable Gate Array (FPGA) circuits only contained a limited amount of logic and operated at a low frequency. Few applications running on FPGAs consumed exc...
We introduce a new, generic framework for private data analysis. The goal of private data analysis is to release aggregate information about a data set while protecting the privac...
The main result of this paper is a near-optimal derandomization of the affine homomorphism test of Blum, Luby and Rubinfeld (Journal of Computer and System Sciences, 1993). We sho...