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Edgar Dobriban
Edgar Dobriban
Statistics & Computer Science, University of Pennsylvania
upenn.edu의 이메일 확인됨 - 홈페이지
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High-dimensional asymptotics of prediction: Ridge regression and classification
E Dobriban, S Wager
The Annals of Statistics, 2015
2892015
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
2892013
A Group-Theoretic Framework for Data Augmentation
S Chen, E Dobriban, JH Lee
NeurIPS 2020 (oral presentation), JMLR, arXiv preprint arXiv:1907.10905, 2019
210*2019
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
1512015
DeltaGrad: Rapid retraining of machine learning models
Y Wu, E Dobriban, SB Davidson
ICML 2020, arXiv preprint arXiv:2006.14755, 2020
1472020
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
862020
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
77*2017
Distributed linear regression by averaging
E Dobriban, Y Sheng
Annals of Statistics, arXiv preprint arXiv:1810.00412, 2018
702018
Jailbreaking black box large language models in twenty queries
P Chao, A Robey, E Dobriban, H Hassani, GJ Pappas, E Wong
arXiv preprint arXiv:2310.08419, 2023
692023
Asymptotics for sketching in least squares regression
E Dobriban, S Liu
Neural Information Processing Systems (NeurIPS) 2019, 2018
62*2018
PCA: high dimensional exponential family PCA
LT Liu, E Dobriban, A Singer
The Annals of Applied Statistics, 2016
602016
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
572022
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
572020
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
57*2019
Ridge Regression: Structure, Cross-Validation, and Sketching
S Liu, E Dobriban
International Conference on Learning Representations (ICLR) 2020, arXiv …, 2019
552019
Permutation methods for factor analysis and PCA
E Dobriban
The Annals of Statistics, 2017
53*2017
Efficient computation of limit spectra of sample covariance matrices
E Dobriban
Random Matrices: Theory and Applications 4 (04), 1550019, 2015
462015
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
372021
Optimal multiple testing under a Gaussian prior on the effect sizes
E Dobriban, K Fortney, SK Kim, AB Owen
Biometrika 102 (4), 753-766, 2015
372015
Optimal prediction in the linearly transformed spiked model
E Dobriban, W Leeb, A Singer
The Annals of Statistics, 2017
36*2017
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