https://rinafb.github.io/ Recent content on Rina Foygel Barber Hugo -- gohugo.io en-us https://rinafb.github.io/group/ Mon, 01 Jan 0001 00:00:00 +0000 https://rinafb.github.io/group/ Group members Zhimei Ren, postdoctoral scholar Jake Soloff, postdoctoral scholar (co-advised with Rebecca Willett) Yuetian Luo, postdoctoral scholar Yonghoon Lee, PhD student Wanrong Zhu, PhD student (co-advised with Wei-Biao Wu) Yu Gui, PhD student Rohan Hore, PhD student Lin Gui, MS student Huanqing Wang, MS student PhD alumni Ang Li (2017), Data Scientist, Twitter Wooseok Ha (2018), ML Scientist, AWS Fan Yang (2019), Hudson River Trading Ran Dai (2020), Assistant Professor, Department of Biostatistics, University of Nebraska Medical Center Haoyang Liu (2020), Hudson River Trading Byol Kim (2021), Postdoctoral Scholar, Department of Statistics, University of Washington Information for prospective students I typically advise one PhD student per year and several Master’s students per year. https://rinafb.github.io/research/ Mon, 01 Jan 0001 00:00:00 +0000 https://rinafb.github.io/research/ Publications & preprints (organized by year) 2023 Conformalized matrix completion. Yu Gui, Rina Foygel Barber, and Cong Ma. arXiv:2305.10637 Pharmacokinetic Analysis of Enhancement-Constrained Acceleration (ECA) reconstruction-based high temporal resolution breast DCE-MRI. Zhen Ren, Ty O. Easley, Federico D. Pineda, Xiaodong Guo, Rina Foygel Barber, and Gregory S. Karczmar. To appear in PLoS ONE. De Finetti’s Theorem and Related Results for Infinite Weighted Exchangeable Sequences. https://rinafb.github.io/software/ Mon, 01 Jan 0001 00:00:00 +0000 https://rinafb.github.io/software/ This page lists software packages only. For code to implement methods and reproduce experiments from individual papers, links to code are placed next to each paper title (go to the Research tab). SEMID: Identifiability of linear structural equation models R package for determining whether the parameters of mixed graphical model are identifiable from the resulting data distribution. (With Mathias Drton.) Related papers: Half-trek criterion for generic identifiability of linear structural equation models, Rina Foygel, Jan Draisma, Mathias Drton (arxiv link). https://rinafb.github.io/talks/ Mon, 01 Jan 0001 00:00:00 +0000 https://rinafb.github.io/talks/ Selected seminars & presentations Distribution-free inference tutorial Video part 1, Video part 2 (At the IFDS 2021 Summer School) “Distribution-free prediction: exchangeability and beyond.” Video (IMS Medallion Lecture 2022) “Is distribution-free inference possible for binary regression?” Video (At the International Seminar on Selective Inference) “Stability of black-box algorithms” Video (Berkeley CLIMB seminar April 2023). https://rinafb.github.io/teaching/ Mon, 01 Jan 0001 00:00:00 +0000 https://rinafb.github.io/teaching/ All course websites are on Canvas and Ed. Current courses Stat 41521: Topics in Distribution-Free Inference (will be taught Autumn 2023). Last year’s syllabus. Stat 27850/30850: Multiple Testing, Modern Inference, and Replicability (will be taught Autumn 2023). Last year’s syllabus. Stat 24400: Statistical Theory and Methods I (most recently taught Winter 2024). a previous year’s syllabus. Past courses Stat 34300: Applied Linear Statistical Methods (most recently taught Autumn 2022).