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We establish a phase transition known as the "all-or-nothing" phenomenon for noiseless discrete channels.
The detection of defective members of large populations
Robert Dorfman · 1943
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Geometric bounds on the Ornstein-Uhlenbeck velocity process
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Convex analysis and minimization algorithms. I
Jean-Baptiste Hiriart-Urruty and Claude Lemaréchal · 1993
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Maxwell construction: The hidden bridge between iterative and maximum a posteriori decoding
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The replica-symmetric prediction for compressed sensing with gaussian matrices is exact
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Statistical physics of inference: thresholds and algorithms
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Reed–muller codes achieve capacity on erasure channels
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Information-theoretic bounds and phase transitions in clustering, sparse PCA, and submatrix localization
Jess Banks, Cristopher Moore, Roman Vershynin, Nicolas Verzelen, and Jiaming Xu · 2018
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Storage capacity in symmetric binary perceptrons
Benjamin Aubin, Will Perkins, and Lenka Zdeborová · 2019
All-or-nothing phenomena: From single-letter to high dimensions
Galen Reeves, Jiaming Xu, and Ilias Zadik · 2019
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The all-or-nothing phenomenon in sparse linear regression
Galen Reeves, Jiaming Xu, and Ilias Zadik · 2019
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Computational and statistical challenges in high dimensional statistical models
Ilias Zadik · 2019
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Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, NeurIPS 2020, December 6-12, 2020, virtual
Hugo Larochelle, Marc’Aurelio Ranzato, Raia Hadsell, Maria-Florina Balcan, and Hsuan-Tien Lin, editors · 2020
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On the all-or-nothing behavior of bernoulli group testing
L. V. Truong, M. Aldridge, and J. Scarlett · 2020
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Optimal errors and phase transitions in high-dimensional generalized linear models
Jean Barbier, Florent Krzakala, Nicolas Macris, Léo Miolane, and Lenka Zdeborová · 2019
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0-1 phase transitions in sparse spiked matrix estimation
Jean Barbier and Nicolas Macris · 2019
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All-or-nothing statistical and computational phase transitions in sparse spiked matrix estimation
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Information theoretic limits of learning a sparse rule
Clément Luneau, Jean Barbier, and Nicolas Macris
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The all-or-nothing phenomenon in sparse tensor PCA
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On the application of the theory of error to cases of normal distribution and normal correlation
William Fleetwood Sheppard
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