WebJun 15, 2024 · Objectives This work aims to study the variation, robustness, and feature redundancy of PET/MR radiomic features in the primary tumor of nasopharyngeal carcinoma (NPC). Procedures PET/MR scans of 21 NPC patients were used in this study. The primary tumor volumes were defined using PET, T2-weighted-MR (T2-MR), and diffusion-weighted … WebJun 12, 2024 · Feature Robustness Feature robustness is supposed to measure the mean change in loss over a dataset under small changes of features in the feature space. Observe that the feature space \mathbb {R}^m Rm can be perturbed by a matrix A \in \mathbb {R}^ {m \times m} A ∈ Rm×m. Measures of Flatness
Feature Robustness and Diagnostic Capabilities of …
WebRobustness is a feature representing the trustworthiness of a neural network model against real-world inputs. The real-world inputs may be from an undesired distribution [32], and are often with distortions or perturbations, either intentionally (e.g., adversarial perturbations [12], [33]) or unintentionally WebA Robustness Evaluation Framework for Feature Attribution". The presenter is Yuyou Gan from Zhejiang University. email: [email protected] mp4. 16.3 MB. Play stream Download. References Julius Adebayo, Justin Gilmer, Michael Muelly, Ian J. Goodfellow, Moritz Hardt, and Been Kim. 2024. Sanity Checks for Saliency Maps. drug monitor
[2304.05294] Selecting Robust Features for Machine Learning ...
Webrobustness noun Definition of robustness 1 as in strength the condition of being sound in body she has the robustness of a woman half her age Synonyms & Similar Words … WebMar 29, 2024 · Feature stability. A feature is an individual property or variable used as an input in an ML system. Consider a model that predicts housing prices. Features may include a house’s location, size, number of bedrooms, previous sale price, or any other number of elements. Frequent variation of important features may impact a model’s stability. Webleveraged to provide both robust features, and a lower bound on the robustness of any function that has significant variance across the dataset. Finally, we provide empirical evidence that the adversarially robust features given by this spectral approach can be fruitfully leveraged to learn a robust (and accurate) model. 1 Introduction drug monitoring spc