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Michael Celentano
Michael Celentano
Miller Fellow (Postdoc), University of California, Berkeley
Zweryfikowany adres z berkeley.edu - Strona główna
Tytuł
Cytowane przez
Cytowane przez
Rok
The lasso with general gaussian designs with applications to hypothesis testing
M Celentano, A Montanari, Y Wei
The Annals of Statistics 51 (5), 2194-2220, 2023
892023
Fundamental barriers to high-dimensional regression with convex penalties
M Celentano, A Montanari
The Annals of Statistics 50 (1), 170-196, 2022
632022
The estimation error of general first order methods
M Celentano, A Montanari, Y Wu
Conference on Learning Theory, 1078-1141, 2020
432020
The high-dimensional asymptotics of first order methods with random data
M Celentano, C Cheng, A Montanari
arXiv preprint arXiv:2112.07572, 2021
362021
Local convexity of the TAP free energy and AMP convergence for -synchronization
M Celentano, Z Fan, S Mei
The Annals of Statistics 51 (2), 519-546, 2023
262023
Sudakov-Fernique post-AMP, and a new proof of the local convexity of the TAP free energy
M Celentano
arXiv preprint arXiv:2208.09550, 2022
152022
CAD: Debiasing the Lasso with inaccurate covariate model
M Celentano, A Montanari
arXiv preprint arXiv:2107.14172, 2021
92021
Approximate separability of symmetrically penalized least squares in high dimensions: characterization and consequences
M Celentano
Information and Inference: A Journal of the IMA 10 (3), 1105-1165, 2021
82021
Minimum complexity interpolation in random features models
M Celentano, T Misiakiewicz, A Montanari
arXiv preprint arXiv:2103.15996, 2021
52021
Mean-field variational inference with the TAP free energy: Geometric and statistical properties in linear models
M Celentano, Z Fan, L Lin, S Mei
arXiv preprint arXiv:2311.08442, 2023
12023
Maximum mean discrepancy meets neural networks: The radon-kolmogorov-smirnov test
S Paik, M Celentano, A Green, RJ Tibshirani
arXiv preprint arXiv:2309.02422, 2023
12023
Challenges of the inconsistency regime: Novel debiasing methods for missing data models
M Celentano, MJ Wainwright
arXiv preprint arXiv:2309.01362, 2023
12023
Exact and efficient phylodynamic simulation from arbitrarily large populations
M Celentano, WS DeWitt, S Prillo, YS Song
arXiv preprint arXiv:2402.17153, 2024
2024
THE ANNALS
PC BELLEC, C ZHANG, A FINKE, AH THIERY, A ROHDE, ...
The Annals of Statistics 51 (2), 2023
2023
Topics in Exact Asymptotics for High-Dimensional Regression
M Celentano
Stanford University, 2021
2021
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