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Edgar Dobriban
Edgar Dobriban
Statistics & Computer Science, University of Pennsylvania
Bestätigte E-Mail-Adresse bei upenn.edu - Startseite
Titel
Zitiert von
Zitiert von
Jahr
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
4282023
High-dimensional asymptotics of prediction: Ridge regression and classification
E Dobriban, S Wager
The Annals of Statistics, 2015
3742015
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
3122013
A Group-Theoretic Framework for Data Augmentation
S Chen, E Dobriban, JH Lee
NeurIPS 2020 (oral presentation), JMLR, arXiv preprint arXiv:1907.10905, 2019
264*2019
DeltaGrad: Rapid retraining of machine learning models
Y Wu, E Dobriban, SB Davidson
ICML 2020, arXiv preprint arXiv:2006.14755, 2020
2352020
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
1632015
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
1122022
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
1032020
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
932024
Distributed linear regression by averaging
E Dobriban, Y Sheng
Annals of Statistics, arXiv preprint arXiv:1810.00412, 2018
872018
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
872017
Asymptotics for sketching in least squares regression
E Dobriban, S Liu
Neural Information Processing Systems (NeurIPS) 2019, 2018
74*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
722020
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
70*2019
Ridge Regression: Structure, Cross-Validation, and Sketching
S Liu, E Dobriban
International Conference on Learning Representations (ICLR) 2020, arXiv …, 2019
662019
Permutation methods for factor analysis and PCA
E Dobriban
The Annals of Statistics, 2017
66*2017
PCA: high dimensional exponential family PCA
LT Liu, E Dobriban, A Singer
The Annals of Applied Statistics, 2016
612016
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
532022
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
532021
Efficient computation of limit spectra of sample covariance matrices
E Dobriban
Random Matrices: Theory and Applications 4 (04), 1550019, 2015
482015
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