The fields of machine learning and mathematical programming are increasingly intertwined. Optimization problems lie at the heart of most machine learning approaches. The Special T...
Grid search and manual search are the most widely used strategies for hyper-parameter optimization. This paper shows empirically and theoretically that randomly chosen trials are ...
We propose a neuro-genetic daily stock prediction model. Traditional indicators of stock prediction are utilized to produce useful input features of neural networks. The genetic al...
We benchmark the pure random search algorithm on the BBOB 2009 noise-free testbed. Each candidate solution is sampled uniformly in [−5, 5]D , where D denotes the search space di...
We benchmark the Pure-Random-Search algorithm on the BBOB 2009 noisy testbed. Each candidate solution is sampled uniformly in [−5, 5]D , where D denotes the search space dimensi...