optimization

Chengjie zhao

Chengjie Zhao

Visiting Researcher, Information Science Lab

Wireless communication Signal processing optimization machine learning

Visiting Student, King Abdullah University of Science and Technology

Chaabane Mankai

M.S. Student, Electrical and Computer Engineering

Wireless Communications optimization Performance analysis network security

Surrounded by bright minds and groundbreaking research, KAUST is a great place to learn and grow.

Ahmed Youssef Ragab Radwan

Visiting Student (former), Information Science Lab

artificial intelligence TinyML optimization deep learning

Visiting student at the Information Science Lab, in the Electrical Engineering Department, CEMSE, King Abdullah University of Science and Technology (KAUST)

Estimating the expected information gain in Bayesian optimal experimental design

May 2, 12:00 - 13:00

B9 L2 H1

optimization DLMC DLMCIS

Optimal experimental design for parameter estimation is a fast-growing area of research. Let us consider the experimental goal to be the inference of some attributes of a complex system using measurement data of some chosen system responses, and the optimal designs are those that maximize the value of measurement data. The value of data is quantified by the expected information gain utility, which measures the informativeness of an experiment. Often, a mathematical model is used that approximates the relationship between the system responses and the model parameters acting as proxies for the attributes of interest.