WebStandard vs. robust generalization. Recent work [11, 16, 5, 7] has focused on the sample complexity of learning a predictor that has high robust accuracy (robust generaliza-tion),adifferentobjective. Incontrast,westudythefinitesam-ple behavior of adversarially trained predictors on the stan-dard learning objective (standard generalization ... WebFeb 11, 2024 · GENSPEC optimizes a single feature-based model for generalization: robust performance across all queries, and many tabular models for specialization: each …
Domain Generalization In Robust Invariant Representation
WebTo better understand this phenomenon, we study adversarially robust learning from the viewpoint of generalization. We show that already in a simple natural data model, the sample complexity of robust learning can be significantly larger than that of "standard" learning. This gap is information theoretic and holds irrespective of the training ... WebApr 30, 2024 · To better understand this phenomenon, we study adversarially robust learning from the viewpoint of generalization. We show that already in a simple natural data model, the sample complexity of robust learning can be … the wthr
Robust Generalization and Safe Query-Specialization in ... - DeepAI
Webrobust optimization (DRO) [36]. Contributions. We highlight the following main contributions of this paper: We introduce a new modelling framework for distribution shifts via the … Webhas already achieved 84%training robustness after 200 epochs (see Figure 1). Its robust generalization gap reaches 41%, which is very different from the standard training (on … WebMay 27, 2024 · By demonstrating an exponential separation between the network size for achieving low robust training and generalization error, our results reveal that the hardness of robust generalization... the wto and gatt: a principled history