Many prediction, decision-making, and control architectures rely on online learned Gaussian process (GP) models. However, most existing GP regression algorithms assume a single generative model, ...

Online learning has witnessed an increasing interest over the recent past due to its low computational requirements and its relevance to a broad range of streaming applications. In this brief, we ...

It should be noted that quantile regression involves a non-differentiable optimization problem with a piecewise linear loss function, also known as the check function. Most existing quantile ...

python linear-regression scikit-learn machine-learning-algorithms ml pca gradient-descent decision-trees naive-bayes-algorithm svm-model linear-regression-models gradient-descent-algorithm ...

machine-learning random-forest linear-regression naive-bayes-classifier logistic-regression convolutional-neural-networks softmax-regression decision-tree-classifier k-means-clustering ...