Georgia Tech's Research Horizons Magazine has done a very nice write-up of the ML@GT center, featuring many of our research projects. Machine learning has been around for decades, but the advent of big data and more powerful computers has increased its impact significantly — moving machine learning beyond pattern recognition and natural language processing into a… Continue reading The Minds of the New Machines | Research Horizons | Georgia Tech’s Research News
Machine learning at Georgia Tech was in the spotlight recently as The Center for Machine Learning at Georgia Tech (ML@GT) hosted its spring seminar on Feb. 22 in the Klaus Advanced Computing Building.Billed as a “day of discussions around machine learning,” more than 200 students and faculty from across campus registered for the daylong event.“AI is… Continue reading Ethics Highlight ‘Day of Machine Learning Discussion’ | College of Computing
We are pleased to have these new faculty join us starting this year. Siva Maguluri CoE / ISyE Devi Parikh CoC / IC Jacob Abernathy CoC / SCS Dhruv Batra CoC / IC Rachel Cummings CoE / ISyE Eva Dyer CoE / BME Wenjing Liao CoS / Math Thomas Ploetz CoC / IC Tuo Zhao… Continue reading Welcome to all the new Machine Learning Faculty to Georgia Tech
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”
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
Machine Learning/Statistics Seminar Series Date/Time: Thursday Sep 7 2017, 11:00 pm - 12:00 pm Location: Advisory Boardroom, #402 Groseclose Speaker: Xiaodong Li Title: Convex Relaxation for Community Detection Abstract: Cluster structures are ubiquitous for large data, and community detection has recently attracted much research attention in applied physics, sociology, computer science and statistics due to… Continue reading ML/Statistics Seminar by Xiaodong Li on “Convex Relaxation for Community Detection”
ML/Statistics Seminar Series Date/Time: Wed. Sep 6 2017, 3:00 pm - 4:00 pm Location: Advisory Boardroom, #402 Groseclose Speaker: Jason Lee Title: Matrix Completion, Saddlepoints, and Gradient Descent Abstract: Matrix completion is a fundamental machine learning problem with wide applications in collaborative filtering and recommender systems. Typically, matrix completion are solved by non-convex optimization procedures,… Continue reading ML/Statistics Seminar by Jason Lee on “Matrix Completion, Saddlepoints, and Gradient Descent”
ML@GT Seminar Series Title: An Overview of Deep Learning Frameworks and an Introduction to PyTorch Speaker: Soumith Chintala, Facebook Date/Time: Wednesday Sep 6 2017, 12:30 pm - 1:30 pm Location: Marcus Nanotechnology Building, Room 1118 Abstract: In this talk, you will get an exposure to the various types of deep learning frameworks – declarative and imperative frameworks such… Continue reading Seminar by Soumith Chintala on “An Overview of Deep Learning Frameworks and an Introduction to PyTorch” 9/6/17, 12:30, Nano 1118
ML@GT hosted a special a seminar & a reception to celebrate Devi’ Parikh’s IJCAI's 2017 Computers and Thought Award. She will give a talk about her work and there will be a reception to celebrate her award. Date/Time: 9/5/2017 @ 3-4pm with a reception following to celebrate this award. Location: The Engineered Biosystems Building (EBB),… Continue reading Devi Parikh gives a seminar to celebrate her IJCAI 2017 Computers and Thought Award.
Machine Learning/Statistics Seminar Series Date/Time: Thursday Aug 31 2017, 11:00 pm - 12:00 pm Location: Advisory Board Room, #402 Groseclose Speaker: Junwei Lu Title: Topological Inference on Large Scale Graphon Abstract: We propose to test the topological structures of complex networks under the graphon model. Graphon is a nonparametric model for large scale stochastic graphs.… Continue reading ML/Statistics Seminar by Junwei Lu on “Topological Inference on Large Scale Graphon”
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