Adversarial Learning

Adversarial learning is a machine learning technique that improves model robustness and fairness by pitting two neural networks against each other—a generator and a discriminator—in a competitive training process. Current research focuses on applications across diverse fields, including improving fairness in predictive analytics, enhancing robustness in reinforcement learning and domain adaptation, and mitigating the effects of adversarial attacks on various models. This approach is significant because it addresses critical limitations of standard machine learning methods, leading to more reliable and equitable outcomes in various applications, from financial risk assessment to medical image analysis and autonomous systems.

Papers

March 29, 2024

CT respiratory motion synthesis using joint supervised and adversarial learning
Yi-Heng Cao, Vincent Bourbonne, François Lucia, Ulrike Schick, Julien Bert, Vincent Jaouen, Dimitris Visvikis
Adversarial Learning 4 Dimensional Patient Specific Multi Phase Respiratory Motion

March 28, 2024

Collaborative Interactive Evolution of Art in the Latent Space of Deep Generative Models
Ole Hall, Anil Yaman
Generative Adversarial Network Latent Space Image Generation Adversarial Learning Art Specific Information Interactive Evolution

March 27, 2024

Towards Sustainable SecureML: Quantifying Carbon Footprint of Adversarial Machine Learning
Syed Mhamudul Hasan, Abdur R. Shahid, Ahmed Imteaj
Machine Learning Native Robustness Adversarial Robustness Adversarial Learning Model Robustness Carbon Footprint

March 26, 2024

March 22, 2024

Robust optimization for adversarial learning with finite sample complexity guarantees
André Bertolace, Konstatinos Gatsis, Kostas Margellos
Adversarial Attack Native Robustness Adversarial Example Adversarial Learning Sample Complexity Robust Optimization Robust Classifier Classifier Robustness

March 17, 2024

A Modified Word Saliency-Based Adversarial Attack on Text Classification Models
Hetvi Waghela, Sneha Rakshit, Jaydip Sen
Adversarial Attack Adversarial Example Adversarial Learning Text Classification Model Traditional Adversarial

March 8, 2024

Exploring the Adversarial Frontier: Quantifying Robustness via Adversarial Hypervolume
Ping Guo, Cheng Gong, Xi Lin, Zhiyuan Yang, Qingfu Zhang
Adversarial Attack Native Robustness Adversarial Robustness Adversarial Learning Adversarial Threat

March 7, 2024

What makes an image realistic?
Lucas Theis
Adversarial Training Generative AI Adversarial Learning Real World Data

March 4, 2024

Improving Adversarial Energy-Based Model via Diffusion Process
Cong Geng, Tian Han, Peng-Tao Jiang, Hao Zhang, Jinwei Chen, Søren Hauberg, Bo Li
Generative Model Generative Adversarial Network Adversarial Learning Energy Based Model Diffusion Process Variational Posterior

February 19, 2024

Manipulating hidden-Markov-model inferences by corrupting batch data
William N. Caballero, Jose Manuel Camacho, Tahir Ekin, Roi Naveiro
Adversarial Learning Hidden Markov Model Adversarial Behavior Adversarial Risk Batch Data

February 15, 2024

Utilizing GANs for Fraud Detection: Model Training with Synthetic Transaction Data
Mengran Zhu, Yulu Gong, Yafei Xiang, Hanyi Yu, Shuning Huo
Generative Adversarial Network Adversarial Learning Model Training Fraud Detection Synthetic Financial

February 5, 2024

Adversarial Data Augmentation for Robust Speaker Verification
Zhenyu Zhou, Junhui Chen, Namin Wang, Lantian Li, Dong Wang
Data Augmentation Adversarial Learning Speaker Embeddings Adversarial Data Augmentation Robust Speaker Verification

January 29, 2024

AdvNF: Reducing Mode Collapse in Conditional Normalising Flows using Adversarial Learning
Vikas Kanaujia, Mathias S. Scheurer, Vipul Arora
Synthetic Data Adversarial Training High Dimensional Adversarial Learning Normalizing Flow Conditional Normalizing Flow Deep Generative Mode Collapse

January 25, 2024

Appearance Debiased Gaze Estimation via Stochastic Subject-Wise Adversarial Learning
Suneung Kim, Woo-Jeoung Nam, Seong-Whan Lee
Adversarial Learning Stochastic Way Gaze Estimation Subject Appearance Appearance Based Gaze Estimation Supervised Gaze

January 24, 2024

January 21, 2024

How Robust Are Energy-Based Models Trained With Equilibrium Propagation?
Siddharth Mansingh, Michal Kucer, Garrett Kenyon, Juston Moore, Michael Teti
Adversarial Attack Adversarial Example Adversarial Training Adversarial Perturbation Adversarial Learning Energy Based Model Equilibrium Propagation

January 19, 2024

Ensembler: Combating model inversion attacks using model ensemble during collaborative inference
Dancheng Liu, Jinjun Xiong
Full Model Adversarial Learning Model Inversion Attack Adversarial Behavior Collaborative Inference LLM Ensemble

January 3, 2024

Adversarial Machine Learning-Enabled Anonymization of OpenWiFi Data
Samhita Kuili, Kareem Dabbour, Irtiza Hasan, Andrea Herscovich, Burak Kantarci, Marcel Chenier, Melike Erol-Kantarci
Generative Adversarial Network Synthetic Data Adversarial Learning Consistent Anonymization Effect Tabular Generative Adversarial Network

Adversarial Learning

Papers

CT respiratory motion synthesis using joint supervised and adversarial learning

Collaborative Interactive Evolution of Art in the Latent Space of Deep Generative Models

Towards Sustainable SecureML: Quantifying Carbon Footprint of Adversarial Machine Learning

Maximum Discrepancy Generative Regularization and Non-Negative Matrix Factorization for Single Channel Source Separation

Boosting Adversarial Training via Fisher-Rao Norm-based Regularization

Robust optimization for adversarial learning with finite sample complexity guarantees

A Modified Word Saliency-Based Adversarial Attack on Text Classification Models

Exploring the Adversarial Frontier: Quantifying Robustness via Adversarial Hypervolume

What makes an image realistic?

Improving Adversarial Energy-Based Model via Diffusion Process

Manipulating hidden-Markov-model inferences by corrupting batch data

Utilizing GANs for Fraud Detection: Model Training with Synthetic Transaction Data

Adversarial Data Augmentation for Robust Speaker Verification

AdvNF: Reducing Mode Collapse in Conditional Normalising Flows using Adversarial Learning

Appearance Debiased Gaze Estimation via Stochastic Subject-Wise Adversarial Learning

Enhancing cross-domain detection: adaptive class-aware contrastive transformer

AdCorDA: Classifier Refinement via Adversarial Correction and Domain Adaptation

How Robust Are Energy-Based Models Trained With Equilibrium Propagation?

Ensembler: Combating model inversion attacks using model ensemble during collaborative inference

Adversarial Machine Learning-Enabled Anonymization of OpenWiFi Data