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Put AI to Work
April 29-30, 2018: Training
April 30-May 2, 2018: Tutorials & Conference
New York, NY
Ameet Talwalkar

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

Website

Ameet Talwalkar is cofounder and chief scientist at Determined AI and an assistant professor in the School of Computer Science at Carnegie Mellon University. His research addresses scalability and ease-of-use issues in the field of statistical machine learning, with applications in computational genomics. Ameet led the initial development of the MLlib project in Apache Spark. He is the coauthor of the graduate-level textbook Foundations of Machine Learning (MIT Press) and teaches an award-winning MOOC on edX, Distributed Machine Learning with Apache Spark.

Sessions

2:35pm–3:15pm Tuesday, May 1, 2018
Scalable deep learning
Models and Methods
 Location: Grand Ballroom East
Ameet Talwalkar (Carnegie Mellon University | Determined AI)
Average rating: ****.
(4.50, 2 ratings)
While deep learning has enjoyed widespread empirical success, fundamental bottlenecks exist when attempting to develop deep learning applications at scale. Ameet Talwalkar shares research on addressing two core scalability bottlenecks: tuning the knobs of deep learning models (i.e., hyperparameter optimization) and training deep models in parallel environments. Read more.