August 2017 – Page 6 – machine-learning-2020

SIMULATION METAMODELING AND OPTIMIZATION WITH AN ADDITIVE GLOBAL AND LOCAL GAUSSIAN PROCESS MODEL FOR STOCHASTIC SYSTEMS

MENG QUN AN ADDITIVE GLOBAL AND LOCAL GAUSSIAN PROCESS MODEL FOR LARGE DATA SETS

Dr NG Szu Hui – Department of Industrial Systems Engineering and Management National University of Singapore

Department of Industrial Systems Engineering and Management Publications

Robert B. Gramacy Professor of Statistics – Virginia Tech

College of Science at Virginia Polytechnic and State University (Virginia Tech) Publications and Technical Reports

ON IMPROVED LEAST SQUARES REGRESSION & ARTIFICIAL NEURAL NETWORK META-MODELS FOR SIMULATION VIA CONTROL VARIATES

Michael P. Gibb

Publications

Machine Learning-Guided Etch Proximity Correction

Geoffrey E. Hinton

Department of Computer Science – University of Toronto Machine Learning at UofT UofT : Machine learning These Publications Yichuan Tang – Learning Generative Models Using Structured Latent Variables

Radford M. Neal

Dept. of Statistics and Dept. of Computer Science, University of Toronto Publications

Learning Generative Models Using Structured Latent Variables

Yichuan Tang

BAYESIAN LEARNING FOR NEURAL NETWORKS

Radford M. Neal

Presentations

Tutorial: Gaussian process models for machine learning-Ed Snelson Tutorial on Gaussian Processes and the Gaussian Process Latent Variable Model – Andreas Damianou Perceptrons and Neural Networks