Deep Learning to Learn

The Machine Learning Center at Georgia Tech (ML@GT) has had a wide variety of guest speakers for our Fall Seminar Series. With the semester drawing to a close, we thought we would throw it back all the way to the very first seminar this semester. In fact, this seminar occurred on the first day of … Continue reading Deep Learning to Learn

Few-shot Learning with Meta-Learning: Progress Made and Challenges Ahead

Hugo Larochelle, a researcher at Google Brain, recently visited Georgia Tech's campus as a part of the Machine Learning Center's Fall Seminar Series. Larochelle drew an enormous crowd with students and faculty filling up the room, leaving many audience members standing or sitting on any patch of carpet they could find. During his talk, "Few-shot … Continue reading Few-shot Learning with Meta-Learning: Progress Made and Challenges Ahead

The Natural Language Decathlon: Multitask Learning as Question Answering

In August 2018, Bryan McCann of Salesforce made the trip from Palo Alto, Calif. to Atlanta, Ga. as a part of the Machine Learning Center at Georgia Tech’s Seminar Series. Students and faculty packed the room to hear McCann present his talk, "The Natural Language Decathlon: Multitask Learning as Question Answering". Abstract Deep learning has improved … Continue reading The Natural Language Decathlon: Multitask Learning as Question Answering

Reaching Beyond Human Accuracy With AI Datacenters

Gregory Diamos of Baidu’s Silicon Valley AI Lab (SVAIL), recently made the trip from Silicon Valley to Atlanta as a part of the Machine Learning Center at Georgia Tech's Seminar Series. Diamos presented his talk, "Reaching Beyond Human Accuracy With AI Datacenters" to a room packed with Georgia Tech students of all levels, faculty members … Continue reading Reaching Beyond Human Accuracy With AI Datacenters

ML@GT Spring Event – 2/22

Please join us on Thursday 2/22/2018 for the ML@GT Center Spring Event featuring talks from internal faculty and invited speakers.  Event runs from 10AM to 5PM in the Klaus Atrium. Invited Speakers Sanjeev Arora     -     Princeton University Sanjeev Arora is Charles C. Fitzmorris Professor of Computer Science at Princeton University. He is interested in … Continue reading ML@GT Spring Event – 2/22

ML/Statistics Seminar by Shama Kakade on “Faster least squares and faster eigenvector computation: Improved algorithms for both optimization and statistics in the big data regime”

ML/Statistics Seminar Series Date/Time: Thursday Sep 28 2017, 11:00 am - 12:00 pmLocation: Advisory Boardroom, #402 Groseclose Speaker: Sham Kakade; Department of Statistics and Computer Science, University of Washington Title: Faster least squares and faster eigenvector computation: Improved algorithms for both optimization and statistics in the big data regime Abstract: Least squares and eigenvector computations … Continue reading ML/Statistics Seminar by Shama Kakade on “Faster least squares and faster eigenvector computation: Improved algorithms for both optimization and statistics in the big data regime”

Seminar by Nathan Silberman on “TF-Slim: A Lightweight Library for Defining, Training and Evaluating Complex Models in TensorFlow” Thursday Sep 7 2017, 4:30 pm – 5:45 pm in Clough 144

ML@GT Seminar and Guest Speaker for CS 7643 Deep Learning Title: TF-Slim: A Lightweight Library for Defining, Training and Evaluating Complex Models in TensorFlow Speaker: Nathan Silberman Date/Time: Thursday Sep 7 2017, 4:30 pm - 5:45 pm Location: Clough 144 Abstract: TF-Slim is a TensorFlow-based library with various components. These include modules for easily defining neural network models … Continue reading Seminar by Nathan Silberman on “TF-Slim: A Lightweight Library for Defining, Training and Evaluating Complex Models in TensorFlow” Thursday Sep 7 2017, 4:30 pm – 5:45 pm in Clough 144