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.
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