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05/14/2023
Local Convergence of Gradient Descent-Ascent for Training Generative Adversarial Networks
Generative Adversarial Networks (GANs) are a popular formulation to trai...
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08/21/2022
Instability and Local Minima in GAN Training with Kernel Discriminators
Generative Adversarial Networks (GANs) are a widely-used tool for genera...
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01/20/2022
Kernel Methods and Multi-layer Perceptrons Learn Linear Models in High Dimensions
Empirical observation of high dimensional phenomena, such as the double ...
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03/08/2021
Asymptotics of Ridge Regression in Convolutional Models
Understanding generalization and estimation error of estimators for simp...
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01/19/2021
Implicit Bias of Linear RNNs
Contemporary wisdom based on empirical studies suggests that standard re...
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05/06/2020
Low-Rank Nonlinear Decoding of μ-ECoG from the Primary Auditory Cortex
This paper considers the problem of neural decoding from parallel neural...
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05/01/2020
Generalization Error of Generalized Linear Models in High Dimensions
At the heart of machine learning lies the question of generalizability o...
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01/26/2020
Inference in Multi-Layer Networks with Matrix-Valued Unknowns
We consider the problem of inferring the input and hidden variables of a...
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11/08/2019
Inference with Deep Generative Priors in High Dimensions
Deep generative priors offer powerful models for complex-structured data...
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03/19/2019
High-Dimensional Bernoulli Autoregressive Process with Long-Range Dependence
We consider the problem of estimating the parameters of a multivariate B...
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03/01/2019
Asymptotics of MAP Inference in Deep Networks
Deep generative priors are a powerful tool for reconstruction problems w...
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08/31/2018
Bilinear Recovery using Adaptive Vector-AMP
We consider the problem of jointly recovering the vector b and the matri...
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06/27/2018
Plug-in Estimation in High-Dimensional Linear Inverse Problems: A Rigorous Analysis
Estimating a vector x from noisy linear measurements Ax+w often requires...
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06/20/2017
Inference in Deep Networks in High Dimensions
Deep generative networks provide a powerful tool for modeling complex da...
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02/26/2016
Learning and Free Energies for Vector Approximate Message Passing
Vector approximate message passing (VAMP) is a computationally simple ap...
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02/25/2016
