Contains slides from my talks.
- Understanding Data Augmentation for Deep Learning and Beyond, Denver, JSM 2019.
- A New Theory for Sketching in Linear Regression, Montreal, 2019.
- How to deal with big data? Understanding large-scale distributed regression, Chicago, 2018. Penn 2018.
- Deterministic parallel analysis: an improved method for selecting factors and principal components, Paris, France 2017. JSM 2018, Vancouver.
- Optimal prediction in the linearly transformed spiked model, Georgia Tech 2017, Atlanta. JSM 2017, Baltimore
- Weighted multiple testing by convex optimization, Xth MCP 2017, Riverside
- ePCA. Exponential Family PCA, Stanford Statistics Seminar, Feb 2017, Stanford University
- Computation, statistics, and random matrix theory, Harvard Probability and Random Matrix Theory Seminar, Oct 2016, Harvard University
- Optimal detection of principal components in high dimensional data, Stanford Statistics Seminar, Aug 2016, Stanford University. 3rd ISNPS conference, June 2016, Avignon. IDEAS seminar May 2016, Princeton
- Multiple testing with prior information identifies loci for exceptional longevity, poster at Big Data in Biomedicine, May 2016, Stanford
- High-dimensional asymptotics of prediction: ridge regression, ML Reading Group, October 2015, Stanford
- Optimal multiple testing with prior information, IXth MCP 2015, Hyderabad