November 9th, 2018 Julis Romo Rabinowitz Building 399, Princeton University This is a one-day workshop on the various aspects of the frontiers of statistics. The workshop intends to bring top researchers together to define and expand the frontiers of statistics. It also provides a focal venue for senior and junior researchers to discuss and outline emerging problems in their fields and to lay the groundwork for future collaborations. Organizers Jianqing Fan, Princeton University Samory Kpotufe, Princeton University Speakers Ery Arias-Castro Afonso Bandeira Jing Lei Andrea Montanari Andrew Nobel Philippe Rigollet Vladimir Spokoiny Ming Yuan Schedule Time Speaker or Event Topic or Activity 8:30am to 9:00am Registration and Breakfast: Julis Romo Rabinowitz 397 9:00am to 9:05am Opening Remarks Session 1: Chair: J. Fan 9:05am to 9:50am Ery Arias-Castro, University of California, San Diego On using graph distances to estimate Euclidean and related distances 9:50am to 10:35am Philippe Rigollet, Massachusetts Institute of Technology Uncoupled isotonic regression via minimum Wasserstein deconvolution 10:35am to 11:00am Coffee Break Julis Romo Rabinowitz 397 Session 2: Chair: Samory Kpotufe 11:00am to 11:45am Andrea Montanari, Stanford University Mean field asymptotics in high-dimensional statistics 11:45am to 12:30pm Ming Yuan, Columbia University Sparse Grid Meets Random Hashing: Learning High Dimensional Functions of Few Variables 12:30pm to 2:00pm Lunch: Sherrerd Hall Atrium 2:00pm to 2:45pm Vladimir Spokoiny, Humboldt University of Berlin Large ball probability with applications to statistical inference Session 3: Chair: Miklos Racz 2:45pm to 3:30pm Afonso Bandeira, New York University Statistical estimation under group actions: The Sample Complexity of Multi-Reference Alignment 3:30pm to 4:00pm Coffee Break Julis Romo Rabinowitz 397 Session 4: Chair: Yuxin Chen 4:00pm to 4:45pm Jing Lei, Carnegie Mellon University Network Representation Using Graph Root Distributions 4:45pm to 5:30pm Andrew Nobel, University of North Carolina at Chapel Hill Variational Analysis of Empirical Risk Minimization Sponsors Operations Research & Financial Engineering Princeton University