Explaining Blended Matching Pursuit: A Multi-Purpose AI Algorithm

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

Making Artificial Intelligence Work in a Changing Environment

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

Explaining Nonparametric Regression on Low Dimensional Manifolds using Deep Neural Networks

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