In this paper, we propose a dynamic mechanism to vary the probability by which fitness inheritance is applied throughout the run of a multi-objective particle swarm optimizer, in ...
We present a general Bayesian framework for hyperparameter tuning in L2-regularized supervised learning models. Paradoxically, our algorithm works by first analytically integratin...
The training of support vector machines (SVM) involves a quadratic programming problem, which is often optimized by a complicated numerical solver. In this paper, we propose a muc...
In this paper, a programming model is presented which enables scalable parallel performance on multi-core shared memory architectures. The model has been developed for application...
A well known industry application that allows controllable processing times is the manufacturing operations on CNC machines. For each turning operation as an example, there is a n...