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11/07/2022
Asymptotics of the Sketched Pseudoinverse
We take a random matrix theory approach to random sketching and show an ...
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05/27/2022
Benign Overparameterization in Membership Inference with Early Stopping
Does a neural network's privacy have to be at odds with its accuracy? In...
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02/02/2022
Parameters or Privacy: A Provable Tradeoff Between Overparameterization and Membership Inference
A surprising phenomenon in modern machine learning is the ability of a h...
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06/14/2021
The Flip Side of the Reweighted Coin: Duality of Adaptive Dropout and Regularization
Among the most successful methods for sparsifying deep (neural) networks...
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10/10/2019
The Implicit Regularization of Ordinary Least Squares Ensembles
Ensemble methods that average over a collection of independent predictor...
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05/28/2019
A Hessian Based Complexity Measure for Deep Networks
Deep (neural) networks have been applied productively in a wide range of...
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03/12/2018
False Discovery Rate Control via Debiased Lasso
We consider the problem of variable selection in high-dimensional statis...
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02/02/2018
An Instability in Variational Inference for Topic Models
Topic models are Bayesian models that are frequently used to capture the...
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10/05/2017
Porcupine Neural Networks: (Almost) All Local Optima are Global
Neural networks have been used prominently in several machine learning a...
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05/08/2017