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09/01/2023
Mechanism of feature learning in convolutional neural networks
Understanding the mechanism of how convolutional neural networks learn f...
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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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02/06/2023
Toward Large Kernel Models
Recent studies indicate that kernel machines can often perform similarly...
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12/28/2022
Feature learning in neural networks and kernel machines that recursively learn features
Neural networks have achieved impressive results on many technological a...
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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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07/14/2022
Benign, Tempered, or Catastrophic: A Taxonomy of Overfitting
The practical success of overparameterized neural networks has motivated...
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06/30/2022
A note on Linear Bottleneck networks and their Transition to Multilinearity
Randomly initialized wide neural networks transition to linear functions...
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05/26/2022
Kernel Ridgeless Regression is Inconsistent for Low Dimensions
We show that kernel interpolation for a large class of shift-invariant k...
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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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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