We present some greedy learning algorithms for building sparse nonlinear regression and classification models from observational data using Mercer kernels. Our objective is to dev...
Prasanth B. Nair, Arindam Choudhury 0002, Andy J. ...
In this paper, we present several baby-step giant-step algorithms for the low hamming weight discrete logarithm problem. In this version of the discrete log problem, we are require...
Oblivious permutation routing in binary d-cubes has been well studied in the literature. In a permutation routing, each node initially contains a packet with a destination such th...
Molecular biological models usually suffer from a dramatic combinatorial blow up. Indeed, proteins form complexes and can modify each others, which leads to the formation of a hug...
In combinatorial optimization, a popular approach to NP-hard problems is the design of approximation algorithms. These algorithms typically run in polynomial time and are guarante...