Edgar Dobriban

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Hamed HassaniUniversity of Pennsylvania (EE, CS, Stat)Correu electrònic verificat a seas.upenn.edu
Insup LeeProfessor, Computer and Information Science, University of PennsylvaniaCorreu electrònic verificat a cis.upenn.edu
Patrick ChaoUniversity of PennsylvaniaCorreu electrònic verificat a wharton.upenn.edu
Alex RobeyPostdoc, Carnegie Mellon UniversityCorreu electrònic verificat a andrew.cmu.edu
Sifan LiuFlatiron InstituteCorreu electrònic verificat a flatironinstitute.org
George PappasUPS Foundation Professor, Electrical and Systems Engineering, University of PennsylvaniaCorreu electrònic verificat a seas.upenn.edu
Yue ShengUniversity of PennsylvaniaCorreu electrònic verificat a sas.upenn.edu
Art OwenProfessor of Statistics, Stanford UniversityCorreu electrònic verificat a stanford.edu
Osbert BastaniUniversity of PennsylvaniaCorreu electrònic verificat a seas.upenn.edu
Xinmeng HuangPhD, University of PennsylvaniaCorreu electrònic verificat a sas.upenn.edu
Susan DavidsonUniversity of PennsylvaniaCorreu electrònic verificat a cis.upenn.edu
Donghwan LeeUniversity of PennsylvaniaCorreu electrònic verificat a sas.upenn.edu
Stefan WagerGraduate School of Business, Stanford UniversityCorreu electrònic verificat a stanford.edu
Sangdon ParkPOSTECH GSAI/CSECorreu electrònic verificat a postech.ac.kr
David HongAssistant Professor, Department of Electrical and Computer Engineering, University of DelawareCorreu electrònic verificat a udel.edu
Amit SingerPrinceton UniversityCorreu electrònic verificat a math.princeton.edu
Shuxiao ChenUniversity of PennsylvaniaCorreu electrònic verificat a wharton.upenn.edu
Jane H. LeeYale UniversityCorreu electrònic verificat a yale.edu
Kristen FortneyBioAge Labs, Stanford University, University of TorontoCorreu electrònic verificat a bioagelabs.com
Eric J Tchetgen TchetgenUniversity ProfessorCorreu electrònic verificat a wharton.upenn.edu

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Edgar Dobriban

Statistics & Computer Science, University of Pennsylvania

Correu electrònic verificat a upenn.edu - Pàgina d'inici

Statistics Machine Learning


Títol Ordena per cites Ordena per any Ordena per títol	Citada per Citada per	Any
Jailbreaking black box large language models in twenty queries P Chao, A Robey, E Dobriban, H Hassani, GJ Pappas, E Wong IEEE Conference on Secure and Trustworthy Machine Learning (SaTML) 2025 …, 2023	497	2023
High-dimensional asymptotics of prediction: Ridge regression and classification E Dobriban, S Wager The Annals of Statistics, 2015	380	2015
Certifying the restricted isometry property is hard AS Bandeira, E Dobriban, DG Mixon, WF Sawin IEEE transactions on information theory 59 (6), 3448-3450, 2013	313	2013
A Group-Theoretic Framework for Data Augmentation S Chen, E Dobriban, JH Lee NeurIPS 2020 (oral presentation), JMLR, arXiv preprint arXiv:1907.10905, 2019	272*	2019
DeltaGrad: Rapid retraining of machine learning models Y Wu, E Dobriban, SB Davidson ICML 2020, arXiv preprint arXiv:2006.14755, 2020	245	2020
Genome-wide scan informed by age-related disease identifies loci for exceptional human longevity K Fortney, E Dobriban, P Garagnani, C Pirazzini, D Monti, D Mari, ... PLoS genetics 11 (12), e1005728, 2015	163	2015
Jailbreakbench: An open robustness benchmark for jailbreaking large language models P Chao, E Debenedetti, A Robey, M Andriushchenko, F Croce, V Sehwag, ... NeurIPS 2024, Datasets and Benchmarks Track, 2024	115	2024
Dynamic load identification for mechanical systems: A review R Liu, E Dobriban, Z Hou, K Qian Archives of Computational Methods in Engineering 29 (2), 831-863, 2022	109	2022
The Implicit Regularization of Stochastic Gradient Flow for Least Squares A Ali, E Dobriban, RJ Tibshirani International Conference on Machine Learning (ICML) 2020, https://arxiv.org …, 2020	105	2020
Deterministic parallel analysis: an improved method for selecting factors and principal components E Dobriban, AB Owen Journal of the Royal Statistical Society, Series B, 2017	87	2017
Distributed linear regression by averaging E Dobriban, Y Sheng Annals of Statistics, arXiv preprint arXiv:1810.00412, 2018	86	2018
Provable tradeoffs in adversarially robust classification E Dobriban, H Hassani, D Hong, A Robey IEEE Transactions on Information Theory (to appear), https://arxiv.org/abs …, 2020	74	2020
WONDER: Weighted one-shot distributed ridge regression in high dimensions E Dobriban, Y Sheng ICML 2020, Journal of Machine Learning Research (JMLR), arXiv preprint arXiv …, 2019	73*	2019
Asymptotics for sketching in least squares regression E Dobriban, S Liu Neural Information Processing Systems (NeurIPS) 2019, 2018	73*	2018
Ridge Regression: Structure, Cross-Validation, and Sketching S Liu, E Dobriban International Conference on Learning Representations (ICLR) 2020, arXiv …, 2019	69	2019
Permutation methods for factor analysis and PCA E Dobriban The Annals of Statistics, 2017	67*	2017
PCA: high dimensional exponential family PCA LT Liu, E Dobriban, A Singer The Annals of Applied Statistics, 2016	61	2016
iDECODe: In-distribution Equivariance for Conformal Out-of-distribution Detection R Kaur, S Jha, A Roy, S Park, E Dobriban, O Sokolsky, I Lee AAAI 2022, arXiv preprint arXiv:2201.02331, 2022	54	2022
What causes the test error? going beyond bias-variance via ANOVA L Lin, E Dobriban Journal of Machine Learning Research 22 (155), 1-82, 2021	53	2021
Efficient computation of limit spectra of sample covariance matrices E Dobriban Random Matrices: Theory and Applications 4 (04), 1550019, 2015	48	2015

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