Many data analysis applications deal with large matrices and involve approximating the matrix using a small number of “components.” Typically, these components are linear combi...
Petros Drineas, Michael W. Mahoney, S. Muthukrishn...
We describe a slightly subexponential time algorithm for learning parity functions in the presence of random classification noise, a problem closely related to several cryptograph...
We describe data structures and algorithms for performing a path-sensitive program analysis to discover equivalences of expressions involving linear arithmetic or uninterpreted fun...
We present a mathematical model for the problem of scheduling tests for core-based system-on-chip (SOC) VLSI designs. Given a set of tests for each core in the SOC and a set of te...
Abstract—Network flow models serve as a popular mathematical framework for the analysis and optimization of Multi-hop Wireless Networks. They also serve to provide the understan...