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20182020
most citedSpectral Graph Matching and Regularized Quadratic Relaxations II: Erdős-Rényi Graphs and Universality

21 citations · 47 across the 5 of their papers we have counts for

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stat.ML2020

Tree-Projected Gradient Descent for Estimating Gradient-Sparse Parameters on Graphs

Sheng Xu, Zhou Fan, Sahand Negahban

We study estimation of a gradient-sparse parameter vector , having strong gradient-sparsity on an underlying g…

stat.ML2020

Spectra of the Conjugate Kernel and Neural Tangent Kernel for linear-width neural networks

Zhou Fan, Zhichao Wang

We study the eigenvalue distributions of the Conjugate Kernel and Neural Tangent Kernel associated to multi-layer feedforward neural networks. In an asymptotic regime where network…

stat.ML201919 cited

Spectral Graph Matching and Regularized Quadratic Relaxations I: The Gaussian Model

Zhou Fan, Cheng Mao, Yihong Wu +1

Graph matching aims at finding the vertex correspondence between two unlabeled graphs that maximizes the total edge weight correlation. This amounts to solving a computationally in…

stat.ML20194 cited

Surfing: Iterative optimization over incrementally trained deep networks

Ganlin Song, Zhou Fan, John Lafferty

We investigate a sequential optimization procedure to minimize the empirical risk functional for certain families of deep network…

stat.ML20193 cited

Iterative Alpha Expansion for estimating gradient-sparse signals from linear measurements

Sheng Xu, Zhou Fan

We consider estimating a piecewise-constant image, or a gradient-sparse signal on a general graph, from noisy linear measurements. We propose and study an iterative algorithm to mi…