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The CP model is extremely useful for interpretation, as we show with an example in neuroscience.
However, it can be difficult to fit to real data for a variety of reasons.
Jonas leads technology development for Open AI’s robotics group, developing methods to apply machine learning and AI to robots.
He also helped build the infrastructure to scale Open AI’s distributed ML systems to thousands of machines.
Apache MXNet is an open-source framework developed for distributed deep learning.
In this talk, we will go over some of the lessons we’ve learned, and how they come together in the design and internals of our system for learning-based robotics research.Her research is generally in the area of computational science and data analysis, with specialties in multilinear algebra and tensor decompositions, graph models and algorithms, data mining, optimization, nonlinear solvers, parallel computing and the design of scientific software.She has received a Presidential Early Career Award for Scientists and Engineers (PECASE), been named a Distinguished Scientist of the Association for Computing Machinery (ACM) and a Fellow of the Society for Industrial and Applied Mathematics (SIAM).Doug leads Magenta, a Google Brain project working to generate music, video, image and text using deep learning and reinforcement learning.A main goal of Magenta is to better understanding how AI can enable artists and musicians to express themselves in innovative new ways.
Anima Anandkumar is a principal scientist at Amazon Web Services and a Bren professor at Caltech CMS department.