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Quantum Computing

  • FDS Colloquium: Brice Huang (MIT), “Algorithmic thresholds in random optimization problems”

    Abstract: Optimizing high-dimensional functions generated from random data is a central problem in modern statistics and machine learning. As these objectives are highly non-convex, the maximum value reachable by efficient algorithms is usually smaller than the maximum value that exists, and characterizing the fundamental computational limits of these problems is a difficult challenge. In this…

  • S&DS Seminar: Adam Smith (BU), “Privacy in Machine Learning and Statistical Inference”

    Zoom Link: https://yale.zoom.us/j/94223816617 Meeting ID: 942 2381 6617 Abstract: The results of learning and statistical inference reveal information about the data they use. This talk discusses the possibilities and limitations of fitting machine learning and statistical models while protecting the privacy of individual records. I will begin by explaining what makes this problem difficult, using…