254 citations · 1.3k across the 50 of their papers we have counts for
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Linear Mode Connectivity and the Lottery Ticket Hypothesis
Jonathan Frankle, Gintare Karolina Dziugaite, Daniel M. Roy +1
We study whether a neural network optimizes to the same, linearly connected minimum under different samples of SGD noise (e.g., random data order and augmentation). We find that st…
In Defense of Uniform Convergence: Generalization via derandomization with an application to interpolating predictors
Jeffrey Negrea, Gintare Karolina Dziugaite, Daniel M. Roy
We propose to study the generalization error of a learned predictor in terms of that of a surrogate (potentially randomized) predictor that is coupled to and desi…
Information-Theoretic Generalization Bounds for SGLD via Data-Dependent Estimates
Jeffrey Negrea, Mahdi Haghifam, Gintare Karolina Dziugaite +2
In this work, we improve upon the stepwise analysis of noisy iterative learning algorithms initiated by Pensia, Jog, and Loh (2018) and recently extended by Bu, Zou, and Veeravalli…
Stochastic Neural Network with Kronecker Flow
Chin-Wei Huang, Ahmed Touati, Pascal Vincent +3
Recent advances in variational inference enable the modelling of highly structured joint distributions, but are limited in their capacity to scale to the high-dimensional setting o…
Stabilizing the Lottery Ticket Hypothesis
Jonathan Frankle, Gintare Karolina Dziugaite, Daniel M. Roy +1
Pruning is a well-established technique for removing unnecessary structure from neural networks after training to improve the performance of inference. Several recent results have…