With 28 papers to present, the Machine Learning Center at Georgia Tech (ML@GT) is poised to make a big splash at the 2020 Neural Processing and Information Systems (NeurIPS) conference. Adding to the excitement is ML@GT faculty member and Dean of Georgia Tech’s College of Computing, Charles Isbell, will give an invited talk. Isbell’s talk,… Continue reading Isbell to Present Keynote at Premier Neural Processing Conference
What once started as a small conference with a few hundred people interested in neural information processing systems has over the years turned into one of the largest artificial intelligence conferences in the world. This year, over 13,000 people attended the 33rd conference on Neural Information Processing Systems (NeurIPS) in Vancouver, British Columbia. Over the… Continue reading Snapshots from NeurIPS2019
By Cyrille Combettes This is an informal summary of our recent paper Blended Matching Pursuit with my advisor Sebastian Pokutta. It will be presented at the Conference on Neural Information Processing Systems (NeurIPS) in Vancouver, British Columbia, Dec. 8-14, 2019. In this post, we motivate and explain the main ideas behind the design of our… Continue reading Explaining Blended Matching Pursuit: A Multi-Purpose AI Algorithm
By Adrian Rivera Cardoso and He Wang Machine learning (ML) is changing our lives. We can instantly translate from one language to another, search entire libraries in a matter of seconds, and even prevent credit card fraud. ML’s success is mostly due to the power of artificial neural networks — a machine learning model inspired… Continue reading Making Artificial Intelligence Work in a Changing Environment
By Minshuo Chen Background and Motivation Deep learning has made significant breakthroughs in various real-world applications, such as computer vision, natural language processing, healthcare, robotics, etc. In image classification, the winner of the $latex 2017$ ImageNet challenge retained a top-$latex 5$ error rate of $latex 2.25\% $ [1], while the data set consists of about… Continue reading Explaining Nonparametric Regression on Low Dimensional Manifolds using Deep Neural Networks
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