Electrical & Computer Engineering
Machine Learning
The ECE Machine Learning group studies the mathematical and algorithmic foundations of machine learning and data science.
Affiliate Appointments
Yingyu Liang
ECE 524 – Introduction to Optimization
ECE 532 – Matrix Methods in Machine Learning
ECE 730 – Modern Probability Theory and Stochastic Processes
CS/ECE 761 – Mathematical Foundations of ML
CS/ECE 861 – Theoretical Foundations of ML
ECE 901 – Special Topics in ECE (ML topics vary by semester)
Systems Information Learning Optimization (SILO) Seminar Series
NIH Center for Predictive Computational Phenotyping
LUCID: NSF-sponsored Graduate Training Program
Optimization theme in the Wisconsin Institute for Discovery
Creating Computers That Can Learn – Interview with Becca Willett
10 Big Ideas for Future NSF Investments
Closing the Loop on Big Data…One Beer at a Time
Catalyzing UW Madison’s Neuroengineering Community
The Science of Funny: Active Machine Learning & Cartoons
How New Yorker Cartoons Could Teach Computers to be Funny
The ECE Machine Learning group studies the mathematical and algorithmic foundations of machine learning and data science.
Affiliate Appointments
Yingyu Liang
ECE 524 – Introduction to Optimization
ECE 532 – Matrix Methods in Machine Learning
ECE 730 – Modern Probability Theory and Stochastic Processes
CS/ECE 761 – Mathematical Foundations of ML
CS/ECE 861 – Theoretical Foundations of ML
ECE 901 – Special Topics in ECE (ML topics vary by semester)
Creating Computers That Can Learn – Interview with Becca Willett
10 Big Ideas for Future NSF Investments
Closing the Loop on Big Data…One Beer at a Time
Catalyzing UW Madison’s Neuroengineering Community
The Science of Funny: Active Machine Learning & Cartoons
How New Yorker Cartoons Could Teach Computers to be Funny