SMU Data Science Review
Volume 3, Number 1 (2020)
Articles
Stationary Exercise Classification using IMUs and Deep Learning
Andrew M. Heroy, Zackary Gill, Samantha Sprague, David Stroud, and John Santerre
Improving Syntactic Relationships Between Language and Objects
Benjamin Wilke, Tej Tenmattam, Anand Rajan, Andrew Pollock, and Joel Lindsey
Optimizing the Enrollment Funnel with Decision Trees and Rule Based List
Stephen Merritt, Anne Francomano, and Martin Garcia
QLIME-A Quadratic Local Interpretable Model-Agnostic Explanation Approach
Steven Bramhall, Hayley Horn, Michael Tieu, and Nibhrat Lohia
Demand Forecasting for Alcoholic Beverage Distribution
Lei Jiang, Kristen M. Rollins, Meredith Ludlow, and Bivin Sadler
Advancing Performance of Retail Recommendation Systems
Lisa Leininger, Johnny Gipson, Kito Patterson, and Brad Blanchard
Demand Forecasting In Wholesale Alcohol Distribution: An Ensemble Approach
Tanvi Arora, Rajat Chandna, Stacy Conant, Bivin Sadler, and Robert Slater
Accelerating Reinforcement Learning with Prioritized Experience Replay for Maze Game
Chaoshun Hu, Mehesh Kuklani, and Paul Panek
sEMG Gesture Recognition With a Simple Model of Attention
John D. Josephs Jr, Carson Drake, Che Cobb, and John Santerre
Universal Vector Neural Machine Translation with Effective Attention
Joshua Yi, Satish Mylapore, Ryan Paul, and Robert Slater
Forecasting San Francisco Bay Area Rapid Transit (BART) Ridership
Swee K. Chew, Alec Lepe, Aaron Tomkins, and Peter Scheirer
Automated Spectroscopic Detection And Mapping Using ALMA and Machine LearningTechniques
Steven Cocke, Andrew Wilkins, Josephine McDaniel, John Santerre, and Conor Nixon
Toxic Comment Classification
Sara Zaheri, Jeff Leath, and David Stroud
