activity
20122024
most citedAdversarial Training Should Be Cast as a Non-Zero-Sum Game

4 citations · 9 across the 8 of their papers we have counts for

collaborators
Showing cs.LGShow all

5 papers · 1 filter

cs.LG2024

Improving SAM Requires Rethinking its Optimization Formulation

Wanyun Xie, Fabian Latorre, Kimon Antonakopoulos +2

This paper rethinks Sharpness-Aware Minimization (SAM), which is originally formulated as a zero-sum game where the weights of a network and a bounded perturbation try to minimize/…

cs.LG2023★ 4 cited

Adversarial Training Should Be Cast as a Non-Zero-Sum Game

Alexander Robey, Fabian Latorre, George J. Pappas +2

One prominent approach toward resolving the adversarial vulnerability of deep neural networks is the two-player zero-sum paradigm of adversarial training, in which predictors are t…

cs.LG2023

OTW: Optimal Transport Warping for Time Series

Fabian Latorre, Chenghao Liu, Doyen Sahoo +1

Dynamic Time Warping (DTW) has become the pragmatic choice for measuring distance between time series. However, it suffers from unavoidable quadratic time complexity when the optim…

cs.LG2022★ 3 cited

Controlling the Complexity and Lipschitz Constant improves polynomial nets

Zhenyu Zhu, Fabian Latorre, Grigorios G Chrysos +1

While the class of Polynomial Nets demonstrates comparable performance to neural networks (NN), it currently has neither theoretical generalization characterization nor robustness…

cs.LG2020★ 1 cited

Efficient Proximal Mapping of the 1-path-norm of Shallow Networks

Fabian Latorre, Paul Rolland, Nadav Hallak +1

We demonstrate two new important properties of the 1-path-norm of shallow neural networks. First, despite its non-smoothness and non-convexity it allows a closed form proximal oper…