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Machine Learning Today and Tomorrow: A Panel Discussion
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Panelists: Peter Bartlett (UC Berkeley; chair), Shai Ben-David (University of Waterloo), Amin Karbasi (Yale University), Andreas Krause (ETH Zurich)
Machine learning has been crucial in developing a wide range of technology, including systems that can understand our spoken commands, recognize objects in images, navigate self-driving cars, and play games like poker and go at a professional level. This semester, the Simons Institute for the Theory of Computing is hosting a program on the theoretical foundations of machine learning that has brought over fifty scientists to Berkeley. This panel will review some of the recent advances in machine learning, explore where the technology is going, and discuss key issues that arise as it plays a larger role in our lives.
This panel was one of over 300 events on campus during Cal Day, a once-a-year opportunity for one and all to experience the stimulating, energetic and multifaceted life of UC Berkeley.
Machine learning has been crucial in developing a wide range of technology, including systems that can understand our spoken commands, recognize objects in images, navigate self-driving cars, and play games like poker and go at a professional level. This semester, the Simons Institute for the Theory of Computing is hosting a program on the theoretical foundations of machine learning that has brought over fifty scientists to Berkeley. This panel will review some of the recent advances in machine learning, explore where the technology is going, and discuss key issues that arise as it plays a larger role in our lives.
This panel was one of over 300 events on campus during Cal Day, a once-a-year opportunity for one and all to experience the stimulating, energetic and multifaceted life of UC Berkeley.
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