Seminar

Bin Yu - Three principles of data science: predictability, stability, and computability

Date
Mon April 16th 2018, 1:10pm
Event Sponsor
Institute for Research in the Social Sciences and Graduate School of Business
Location
Rm. C102, MBA Class of 1968, Stanford Graduate School of Business
Bin Yu - Three principles of data science: predictability, stability, and computability
Talk title: Three principles of data science: predictability, stability, and computability
 
Abstract: In this talk, I'd like to discuss the intertwining importance and connections of three principles of data science in the title. They will be demonstrated in the context of two collaborative projects in neuroscience and genomics, respectively. The first project in neuroscience uses transfer learning to integrate fitted convolutional neural networks (CNNs) on ImageNet with regression methods to provide predictive and stable characterizations of neurons from the challenging primary visual cortex V4. The second project proposes iterative random forests (iRF) as a stablized RF to seek predictable and interpretable high-order interactions among biomolecules.