The 2nd Midwest Statistical Machine Learning Colloquium

May 13, 2019

This is a one-day regional meeting of statisticians, engineers, computer scientists, mathematicians, and practitioners interested in the theory and applications of Statistical Machine Learning.  The colloquim is being organized by the Iowa State University Departments of Industrial & Manufacturing Systems Engineering and Department of Statistics.

Purpose:  Bring together a diverse set of researchers and practitioners from multiple disciplines to discuss current motivating problems and methodological advances in theory-based machine learning.


Agenda

Keynote Speakers include:

Andrew Kuhl, Syngenta Seeds

Presentation Title: Improving decision-making in plant breeding through data science and analytics

Lizhen Lin, University of Notre Dame

Presentation Title: High-dimensional Covariance Structure Testing using Maximum Pairwise Bayes Factors

Markus Sauter, Principal Global Equities

Presentation Title: From data to investable product, a quantitative investment journey.

Nick Street, University of Iowa

Presentation Title: Inverse Classification: Better Algorithms for Better Decision Making

Shiyu Zhou, University of Wisconsin-Madison

Presentation Title: Advances in Data Analytics for IoT Enabled Smart and Connected Systems

Hui Zou, University of Minnesota

Presentation Title: A Magic CV Theory for the SVM and Related Large Margin Classifiers

Event Type

Host

Iowa State University Departments of Industrial & Manufacturing Systems Engineering and Department of Statistics

Sponsor

Principal Financial
National Institute of Statistical Sciences
American Statistical Association Section on Statistical Learning and Data Science
Kingland Data Analytics Faculty Fellowship

Location

Iowa State University
Howe Hall
537 Bissell Road
Ames
,
Iowa
,
50011-1096
United States
The 2nd Midwest Statistical Machine Learning Colloquium