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2002.12903
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The estimation error of general first order methods
Annual Conference Computational Learning Theory (COLT), 2020
28 February 2020
Michael Celentano
Andrea Montanari
Yuchen Wu
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Papers citing
"The estimation error of general first order methods"
30 / 30 papers shown
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Unifying AMP Algorithms for Rotationally-Invariant Models
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Linear Operator Approximate Message Passing (OpAMP)
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Semidefinite programs simulate approximate message passing robustly
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Sampling with flows, diffusion and autoregressive neural networks: A spin-glass perspective
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Bayes optimal learning in high-dimensional linear regression with network side information
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Algorithmic Decorrelation and Planted Clique in Dependent Random Graphs: The Case of Extra Triangles
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Optimal Algorithms for the Inhomogeneous Spiked Wigner Model
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Justin Ko
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Equivalence of Approximate Message Passing and Low-Degree Polynomials in Rank-One Matrix Estimation
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Alexander S. Wein
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Lower Bounds for the Convergence of Tensor Power Iteration on Random Overcomplete Models
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Learning curves for the multi-class teacher-student perceptron
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Bayesian Inference with Nonlinear Generative Models: Comments on Secure Learning
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Ali Bereyhi
Bruno Loureiro
Florent Krzakala
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Statistically Optimal First Order Algorithms: A Proof via Orthogonalization
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Yuchen Wu
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Towards Designing Optimal Sensing Matrices for Generalized Linear Inverse Problems
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