Abstract--We give sublinear-time approximation algorithms for some optimization problems arising in machine learning, such as training linear classifiers and finding minimum enclos...
Kenneth L. Clarkson, Elad Hazan, David P. Woodruff
Runtime data alignment has been paid attention recently since it can allocate data segment to processors dynamically according to applications' requirement. One of the key opt...
We study the problem of scheduling permanent jobs on unrelated machines when the objective is to minimize the Lp norm of the machine loads. The problem is known as load balancing ...
— In this paper a new approach to optimize nuclear power plant designs based on global risk reduction are described. In design the focus is on as components quality as redundancy...
Abstract. In this paper, we propose a general framework for designing fully polynomial time approximation schemes for combinatorial optimization problems, in which more than one ob...