Adversarial Framework

Adversarial frameworks are a class of machine learning techniques that leverage competition between two or more models to improve robustness, interpretability, or other desirable properties. Current research focuses on applying these frameworks to diverse areas, including improving the robustness of deep neural networks (DNNs) against adversarial attacks, enhancing the security of large language models (LLMs), and developing more reliable anomaly detection methods. These techniques are significant because they address critical vulnerabilities in existing machine learning systems, leading to more reliable and trustworthy AI applications across various domains.

Papers

March 23, 2023

Generative Image Inpainting with Segmentation Confusion Adversarial Training and Contrastive Learning
Zhiwen Zuo, Lei Zhao, Ailin Li, Zhizhong Wang, Zhanjie Zhang, Jiafu Chen, Wei Xing, Dongming Lu
Contrastive Learning Adversarial Training Adversarial Framework Adversarial Game Standard Adversarial Training Generative Image

January 16, 2023

Continuous Trajectory Generation Based on Two-Stage GAN
Wenjun Jiang, Wayne Xin Zhao, Jingyuan Wang, Jiawei Jiang
Handwritten Trajectory Trajectory Generation Human Mobility Adversarial Framework Stage GAN

January 4, 2023

Towards Explainable Land Cover Mapping: a Counterfactual-based Strategy
Cassio F. Dantas, Diego Marcos, Dino Ienco
Counterfactual Explanation Land Cover Adversarial Framework Satellite Image Time Series Counterfactual Generative

November 14, 2022

IFQA: Interpretable Face Quality Assessment
Byungho Jo, Donghyeon Cho, In Kyu Park, Sungeun Hong
Adversarial Framework Face Restoration Face Image Quality Assessment Face Quality

October 20, 2022

Learning Sample Reweighting for Accuracy and Adversarial Robustness
Chester Holtz, Tsui-Wei Weng, Gal Mishne
Adversarial Training Adversarial Robustness Adversarial Perturbation Robust Generalization Adversarial Framework Sample Reweighting

October 8, 2022

Robustness of Unsupervised Representation Learning without Labels
Aleksandar Petrov, Marta Kwiatkowska
Native Robustness Label Information Unsupervised Representation Learning Adversarial Framework Learning Benchmark Robust Unsupervised Robust Encoders

October 7, 2022

Images as Weight Matrices: Sequential Image Generation Through Synaptic Learning Rules
Kazuki Irie, Jürgen Schmidhuber
U Net Natural Image Weight Matrix Adversarial Framework Image Generator Local Learning Rule

September 29, 2022

Regularizing Neural Network Training via Identity-wise Discriminative Feature Suppression
Avraham Chapman, Lingqiao Liu
Neural Network Generalization Performance Adversarial Framework Feature Suppression Low Training Error

July 14, 2022

Forcing the Whole Video as Background: An Adversarial Learning Strategy for Weakly Temporal Action Localization
Ziqiang Li, Yongxin Ge, Jiaruo Yu, Zhongming Chen
Reinforcement Learning Temporal Action Localization Background Knowledge Action Localization Adversarial Framework Video Level Whole Video

July 9, 2022

July 3, 2022

Anomaly Detection with Adversarially Learned Perturbations of Latent Space
Vahid Reza Khazaie, Anthony Wong, John Taylor Jewell, Yalda Mohsenzadeh
Anomaly Detection Latent Space Supervised Autoencoder Unsupervised Anomaly Detection Adversarial Framework

June 23, 2022

A novel adversarial learning strategy for medical image classification
Zong Fan, Xiaohui Zhang, Jacob A. Gasienica, Jennifer Potts, Su Ruan, Wade Thorstad, Hiram Gay, Pengfei Song, Xiaowei Wang, Hua Li
Medical Image Classification Adversarial Framework Auxiliary Network

June 17, 2022

Avoid Overfitting User Specific Information in Federated Keyword Spotting
Xin-Chun Li, Jin-Lin Tang, Shaoming Song, Bingshuai Li, Yinchuan Li, Yunfeng Shao, Le Gan, De-Chuan Zhan
Deep Learning Model Speech Data Model Overfitting Keyword Spotting Adversarial Framework

May 20, 2022

Towards Consistency in Adversarial Classification
Laurent Meunier, Raphaël Ettedgui, Rafael Pinot, Yann Chevaleyre, Jamal Atif
Adversarial Example Strong Consistency Generative Adversarial Adversarial Framework Adversarial Consistency

April 11, 2022

medXGAN: Visual Explanations for Medical Classifiers through a Generative Latent Space
Amil Dravid, Florian Schiffers, Boqing Gong, Aggelos K. Katsaggelos
Latent Space Medical Image Visual Explanation Adversarial Framework Latent Space Interpolation

February 19, 2022

Deep Single Image Deraining using An Asymetric Cycle Generative and Adversarial Framework
Wei Liu, Rui Jiang, Cheng Chen, Tao Lu, Zixiang Xiong
Generative Adversarial Network Image Deraining Adversarial Framework Rain Fog Feature Extraction

December 31, 2021

Conditional Generative Data-free Knowledge Distillation
Xinyi Yu, Ling Yan, Yang Yang, Libo Zhou, Linlin Ou
Knowledge Distillation Data Free Knowledge Distillation Adversarial Framework Conditional Image Generation

December 10, 2021

Cross-Modal Transferable Adversarial Attacks from Images to Videos
Zhipeng Wei, Jingjing Chen, Zuxuan Wu, Yu-Gang Jiang
Adversarial Attack Adversarial Example Gameplay Video Transferable Adversarial Attack Adversarial Framework Modal Attack

November 9, 2021

Wasserstein Adversarially Regularized Graph Autoencoder
Huidong Liang, Junbin Gao
Link Prediction Adversarial Framework Graph AutoEncoder Wasserstein Dictionary Implicit Generative