Explaining Vulnerabilities to Adversarial Machine Learning through
Visual Analytics

Explaining Vulnerabilities to Adversarial Machine Learning through Visual Analytics

17 July 2019

Ross Maciejewski

Papers citing "Explaining Vulnerabilities to Adversarial Machine Learning through Visual Analytics"

16 / 16 papers shown

Title
TRIVEA: Transparent Ranking Interpretation using Visual Explanation of Black-Box Algorithmic Rankers Jun Yuan Kaustav Bhattacharjee A. Islam Aritra Dasgupta 28 2 0 28 Aug 2023
LINGO : Visually Debiasing Natural Language Instructions to Support Task Diversity Anjana Arunkumar Shubham Sharma Rakhi Agrawal Sriramakrishnan Chandrasekaran Chris Bryan 34 0 0 12 Apr 2023
DeforestVis: Behavior Analysis of Machine Learning Models with Surrogate Decision Stumps Angelos Chatzimparmpas Rafael M. Martins A. Telea Andreas Kerren 24 2 0 31 Mar 2023
The State of the Art in Enhancing Trust in Machine Learning Models with the Use of Visualizations Angelos Chatzimparmpas R. Martins I. Jusufi K. Kucher Fabrice Rossi A. Kerren FAtt 26 160 0 22 Dec 2022
HardVis: Visual Analytics to Handle Instance Hardness Using Undersampling and Oversampling Techniques Angelos Chatzimparmpas F. Paulovich Andreas Kerren 32 6 0 29 Mar 2022
Poisoning Attacks and Defenses on Artificial Intelligence: A Survey M. A. Ramírez Song-Kyoo Kim H. A. Hamadi Ernesto Damiani Young-Ji Byon Tae-Yeon Kim C. Cho C. Yeun AAML 25 37 0 21 Feb 2022
STARdom: an architecture for trusted and secure human-centered manufacturing systems Jože M. Rožanec Patrik Zajec K. Kenda I. Novalija B. Fortuna ... Diego Reforgiato Recupero D. Kyriazis G. Sofianidis Spyros Theodoropoulos John Soldatos 31 7 0 02 Apr 2021
FeatureEnVi: Visual Analytics for Feature Engineering Using Stepwise Selection and Semi-Automatic Extraction Approaches Angelos Chatzimparmpas Rafael M. Martins Kostiantyn Kucher Andreas Kerren 37 21 0 26 Mar 2021
Explainable Adversarial Attacks in Deep Neural Networks Using Activation Profiles G. Cantareira R. Mello F. Paulovich AAML 24 9 0 18 Mar 2021
A Visual Analytics Framework for Explaining and Diagnosing Transfer Learning Processes Yuxin Ma Arlen Fan Jingrui He A. R. Nelakurthi Ross Maciejewski 17 25 0 15 Sep 2020
A Survey of Visual Analytics Techniques for Machine Learning Jun Yuan Changjian Chen Weikai Yang Mengchen Liu Jiazhi Xia Shixia Liu 21 216 0 21 Aug 2020
Diagnosing Concept Drift with Visual Analytics Weikai Yang Zhuguo Li Mengchen Liu Yafeng Lu Kelei Cao Ross Maciejewski Shixia Liu 47 33 0 28 Jul 2020
StackGenVis: Alignment of Data, Algorithms, and Models for Stacking Ensemble Learning Using Performance Metrics Angelos Chatzimparmpas Rafael M. Martins Kostiantyn Kucher Andreas Kerren DiffM BDL 27 75 0 04 May 2020
Analyzing the Noise Robustness of Deep Neural Networks Kelei Cao Mengchen Liu Hang Su Jing Wu Jun Zhu Shixia Liu AAML 60 89 0 26 Jan 2020
Revealing Neural Network Bias to Non-Experts Through Interactive Counterfactual Examples Chelsea M. Myers Evan Freed Luis Fernando Laris Pardo Anushay Furqan S. Risi Jichen Zhu CML 13 12 0 07 Jan 2020
ShapeShifter: Robust Physical Adversarial Attack on Faster R-CNN Object Detector Shang-Tse Chen Cory Cornelius Jason Martin Duen Horng Chau ObjD 165 424 0 16 Apr 2018