Speaker: Ming Zhong, assistant professor, Department of Applied Math, Illinois Institute of Technology Title: How Scientific Machine Learning Can Be Used for Knowledge Discovery? Abstract: Identifying...
Speaker: Simon Mak, Assistant Professor, Department of Statistical Science at Duke University Title: Population Quasi-Monte Carlo Abstract: Monte Carlo methods are widely used for approximating...
Join faculty from Illinois Institute of Technology and Rust College for an online panel discussion "What is Data Science, and Why Is Important?" Moderated by Shlomo Argamon, 91×ÔÅÄ professor of...
Speaker: Professor Ilse Ipsen, Department of Mathematics at North Carolina State University Title: BayesCG: A probabilistic numeric linear solver Abstract: We present the probabilistic numeric solver...
Speaker: Huiyuan Yu, Ph.D., Illinois Institute of Technology Title: Compressed Sensing: Algorithms and Convergence Properties Abstract: Compressive sensing (CS) states that a sparse signal can be...
Speaker: Jia He, PHD, Illinois Institute of Technology Title: Machine Learning on Graphs: Graph Signal Processing and Graph Substructure Learning Abstract: Machine learning on graphs is an interesting...
Speaker: Jiehuan Sun, Assistant professor, University of Illinois Chicago Title: Learning Healthcare Delivery Network with Longitudinal Electronic Health Records Data Abstract: Knowledge networks such...
Title: Towards Third Wave AI: Interpretable, Robust Trustworthy Machine Learning for Diverse Applications in Science and Engineering Speaker: Guang Lin, Professor Departments of Mathematics...
Title: Bayesian Model Calibration and Sensitivity Analysis for Oscillating Biological Experiments Speaker: Youngdeok Hwang, Paul H. Chook Department of Information System and Statistics in the Zicklin...
Speaker: Sifan Liu, PHD, statistics department, Stanford University Title: Quasi-Monte Carlo Quasi-Newton for Variational Bayes Abstract: Many machine learning problems optimize an objective that must...
