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cs.LG2022★ 3 cited
Learning Sample Reweighting for Accuracy and Adversarial Robustness
Chester Holtz, Tsui-Wei Weng, Gal Mishne
There has been great interest in enhancing the robustness of neural network classifiers to defend against adversarial perturbations through adversarial training, while balancing th…
cs.LG2022
Evaluating Disentanglement in Generative Models Without Knowledge of Latent Factors
Chester Holtz, Gal Mishne, Alexander Cloninger
Probabilistic generative models provide a flexible and systematic framework for learning the underlying geometry of data. However, model selection in this setting is challenging, p…