Please Note: This seminar will be given in-person.
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Distinguished Lecture Trevor Hastie Room: DC 1302 |
Some Comments on CV
Please Note: This seminar will be given in person.
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Statistics and Biostatistics seminar series Elena Tuzhilina Room: M3 3127 |
Statistical curve models for inferring 3D chromatin architecture
Please Note: This seminar will be given in-person.
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Distinguished Lecture Series Vladimir Vovk Room: DC 1302 |
Nonparametric prediction and testing
The assumption of randomness (the data are generated in the IID fashion) is the key assumption used in machine learning and much of nonparametric statistics. My main topics will be prediction under this assumption and testing the assumption. The treatment of both topics will be based on the relatively recent technique of conformal prediction, but I will try to connect it with David A. Sprott's ideas and areas of research pointing out some paradoxical features of prediction and testing in the framework of unrestricted randomness. On one hand, they are barely possible, in the sense that the existence of non-trivial prediction and testing procedures is fragile: they cease to exist when the problem settings are modified in natural ways. On the other, such procedures can be highly efficient in realistic situations; I will give both theoretical and experimental results demonstrating this.
Please Note: This seminar will be given in person.
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Statistics and Biostatistics seminar series Qingrun Zhang Room: M3 3127 |
Stabilized Core gene and Pathway Election uncovers pan-cancer shared pathways and a cancer-specific driver
