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The Franz-Parisi Criterion and Computational Trade-offs in High Dimensional Statistics


May 19, 2022
Afonso S. Bandeira, Ahmed El Alaoui, Samuel B. Hopkins, Tselil Schramm, Alexander S. Wein, Ilias Zadik

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* 51 pages, 1 figure 

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A Robust Spectral Algorithm for Overcomplete Tensor Decomposition


Mar 05, 2022
Samuel B. Hopkins, Tselil Schramm, Jonathan Shi

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* Proceedings of the Thirty-Second Conference on Learning Theory. PMLR. p. 1683--1722. 2019 
* 60 pages, 4 figures, ACM Annual Workshop on Computational Learning Theory 2019 

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Robust Regression Revisited: Acceleration and Improved Estimation Rates


Jun 22, 2021
Arun Jambulapati, Jerry Li, Tselil Schramm, Kevin Tian

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* 47 pages 

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Non-asymptotic approximations of neural networks by Gaussian processes


Feb 17, 2021
Ronen Eldan, Dan Mikulincer, Tselil Schramm

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* 18 pages 

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Statistical Query Algorithms and Low-Degree Tests Are Almost Equivalent


Sep 13, 2020
Matthew Brennan, Guy Bresler, Samuel B. Hopkins, Jerry Li, Tselil Schramm

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Computational Barriers to Estimation from Low-Degree Polynomials


Aug 05, 2020
Tselil Schramm, Alexander S. Wein

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* 38 pages 

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High-dimensional estimation via sum-of-squares proofs


Jul 30, 2018
Prasad Raghavendra, Tselil Schramm, David Steurer

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(Nearly) Efficient Algorithms for the Graph Matching Problem on Correlated Random Graphs


May 07, 2018
Boaz Barak, Chi-Ning Chou, Zhixian Lei, Tselil Schramm, Yueqi Sheng

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Fast and robust tensor decomposition with applications to dictionary learning


Jun 27, 2017
Tselil Schramm, David Steurer

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Fast spectral algorithms from sum-of-squares proofs: tensor decomposition and planted sparse vectors


Feb 03, 2016
Samuel B. Hopkins, Tselil Schramm, Jonathan Shi, David Steurer

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* 62 pages, title changed, to appear at STOC 2016 

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