Presentations at 3rd Workshop on Adversarial Learning Methods for Machine Learning and Data Mining

Описание: Recording of 3rd Workshop on Adversarial Learning Methods for Machine Learning and Data Mining (AdvML'2021), a virtual workshop co-located at ACM KDD 2021

Workshop Link: https://sites.google.com/view/advml

List of accepted papers:
Vito Walter Anelli (Polytechnic University of Bari); Yashar Deldjoo (Polytechnic University of Bari); Tommaso Di Noia (Politecnico di Bari); Felice Antonio Merra (Politecnico di Bari). Understanding the Effects of Adversarial Personalized Ranking Optimization Method on Recommendation Quality [MIT IBM Watson AI Lab Best Paper Award]

David Stutz (Max Planck Institute for Informatics); Matthias Hein (University of Tübingen); Bernt Schiele (MPI Informatics). Relating Adversarially Robust Generalization to Flat Minima

David Stutz (Max Planck Institute for Informatics); Nandhini Chandramoorthy (IBM T. J. Watson Research Center); Matthias Hein (University of Tübingen); Bernt Schiele (MPI Informatics). Bit Error Robustness for Energy-Efficient DNN Accelerators

Nimrah Shakeel. Context-Free Word Importance Scores for Attacking Neural Networks

Jacob M Springer (Los Alamos National Laboratory); Bryn Reinstadler (MIT); Una-May O'Reilly (MIT). STRATA: Simple, Gradient-Free Attacks for Models of Code

Clayton B Washington (The Ohio State University); Maximum Wilder-Smith (California State Polytechnic University at Pomona); Tingting Chen (California State Polytechnic University at Pomona); Hao Ji (California State Polytechnic University at Pomona). Robust Localized Physical Attacks on Deep Learning Classifiers for Objects with Arbitrary Surface

Ankita Shukla (Arizona State University); Pavan Turaga (Arizona State University); Saket Anand (Indraprastha Institute of Information Technology Delhi). Cleaning Adversarial Perturbations with Image-Subspace Projections

Yize Li (Northeastern University); Pu Zhao (Northeastern University); Yao Yuguang (Michigan State University); Vishal Asnani (Michigan State University); Yifan Gong (Northeastern University); Yimeng Zhang (Michigan State University); Zhengang Li (Northeastern University); Xiaoming Liu (Michigan State University); Sijia Liu (Michigan State University); Xue Lin (Northeastern University). Supervised Classification on Deep Neural Network Attack Toolchains

Chenan Wang (Northeastern University); Pu Zhao (Northeastern University); Siyue Wang (Northeastern University); Xue Lin (Northeastern University). Detection and Recovery Against Deep Neural Network Fault Injection Attacks Based on Contrastive Learning

Gihyuk Ko (Carnegie Mellon University); Gyumin Lim (Korea Advanced Institute of Science and Technology). Unsupervised Detection of Adversarial Examples with Model Explanations