Presented By
O’Reilly + Intel AI
Put AI to Work
April 15-18, 2019
New York, NY
Discover opportunities for applied AI
Organizations that successfully apply AI innovate and compete more effectively. How is AI transforming your business?
Be a part of the program—apply to speak by October 16.
Ameet Talwalkar

Ameet Talwalkar
Assistant Professor ; Cofounder and Chief Scientist, Carnegie Mellon University and Determined AI

Website

Ameet Talwalkar is co-founder and chief scientist at Determined AI and an assistant professor in the Machine Learning Department at Carnegie Mellon University. His primary interests are in the field of statistical machine learning, including problems at the intersection of systems and learning. He helped to create the SysML conference, led the initial development of the MLlib project in Apache Spark, is the coauthor of the graduate-level textbook Foundations of Machine Learning (MIT Press), and teaches an award-winning MOOC called Distributed Machine Learning with Apache Spark (edX).

Sessions

1:00pm1:40pm Wednesday, April 17, 2019
Machine Learning, Models and Methods
Location: Grand Ballroom West
Secondary topics:  Automation in machine learning and AI, Deep Learning and Machine Learning tools, Models and Methods
Ameet Talwalkar (Carnegie Mellon University and Determined AI)
Hyperparameter tuning is a crucial, yet expensive, component of the ML development lifecycle. Given the growing costs of model training, we would like to leverage parallelism to tune models in roughly the same wall-clock time needed to train a single model. We propose an elegant solution to this problem, and present extensive experimental results supporting the effectiveness of our approach. Read more.