Active learning Bayesian support vector regression model for global approximation

An active multi-class classification using privileged information and belief function

(2019) Mitra Javid et al.   International Journal of Machine Learning and Cybernetics

Semi-supervised active learning for support vector machines: A novel approach that exploits structure information in data

(2018) Adrian Calma et al.   INFORMATION SCIENCES

Bayesian deep convolutional encoder–decoder networks for surrogate modeling and uncertainty quantification

(2018) Yinhao Zhu et al.   JOURNAL OF COMPUTATIONAL PHYSICS

Large-scale support vector regression with budgeted stochastic gradient descent

(2018) Zongxia Xie et al.   International Journal of Machine Learning and Cybernetics

Deep UQ: Learning deep neural network surrogate models for high dimensional uncertainty quantification

(2018) Rohit K. Tripathy et al.   JOURNAL OF COMPUTATIONAL PHYSICS

An l1-norm loss based twin support vector regression and its geometric extension

(2018) Xinjun Peng et al.   International Journal of Machine Learning and Cybernetics

An adaptive sampling method for global sensitivity analysis based on least-squares support vector regression

(2018) M. Steiner et al.   RELIABILITY ENGINEERING & SYSTEM SAFETY

Incorporating Diversity and Informativeness in Multiple-Instance Active Learning

(2017) Ran Wang et al.   IEEE TRANSACTIONS ON FUZZY SYSTEMS

Machine learning of linear differential equations using Gaussian processes

(2017) Maziar Raissi et al.   JOURNAL OF COMPUTATIONAL PHYSICS

Maximum likelihood optimal and robust Support Vector Regression with lncosh loss function

(2017) Omer Karal   NEURAL NETWORKS

A survey of adaptive sampling for global metamodeling in support of simulation-based complex engineering design

(2017) Haitao Liu et al.   STRUCTURAL AND MULTIDISCIPLINARY OPTIMIZATION

An efficient reliability method combining adaptive Support Vector Machine and Monte Carlo Simulation

(2017) Qiujing Pan et al.   STRUCTURAL SAFETY

Rare-event probability estimation with adaptive support vector regression surrogates

(2016) J.-M. Bourinet   RELIABILITY ENGINEERING & SYSTEM SAFETY

A new and informative active learning approach for support vector machine

(2013) Lisha Hu et al.   INFORMATION SCIENCES

Sparse multikernel support vector regression machines trained by active learning

(2012) V. Ceperic et al.   EXPERT SYSTEMS WITH APPLICATIONS

Approximate Confidence and Prediction Intervals for Least Squares Support Vector Regression

(2010) Kris De Brabanter et al.   IEEE TRANSACTIONS ON NEURAL NETWORKS