Logistic Regression (LR) has been widely used in statistics for many years, and has received extensive study in machine learning community recently due to its close relations to S...
Jian Zhang, Rong Jin, Yiming Yang, Alexander G. Ha...
Recent years have seen growth in the number of algorithms designed to solve challenging simulation-based nonlinear optimization problems. One such algorithm is the Trust-Region Par...
In this paper we introduce a mesh approximation method that uses a volume-based metric. After a geometric simplification, we minimize the volume between the simplified mesh and th...
Pierre Alliez, Nathalie Laurent, Henri Sanson, Fra...
We consider a stochastic variant of the NP-hard 0/1 knapsack problem in which item values are deterministic and item sizes are independent random variables with known, arbitrary d...
Brian C. Dean, Michel X. Goemans, Jan Vondrá...
We address power minimization of earliest deadline first and ratemonotonic schedules by voltage and frequency scaling. We prove that the problems are NP-hard, and present (1+ ) f...