Publications related to Adversarial machine learning

A Methodology for Evaluating the Robustness of Anomaly Detectors to Adversarial Attacks in Industrial Scenarios

Anomaly Detection systems based on Machine and Deep learning are the most promising solutions to detect cyberattacks in the industry. However, these techniques are vulnerable to adversarial attacks that downgrade prediction performance. Several techniques ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2022

Byzantine Machine Learning Made Easy By Resilient Averaging of Momentums

Rachid Guerraoui, Nirupam Gupta, John Stephan, Sadegh Farhadkhani, Rafaël Benjamin Pinot

Byzantine resilience emerged as a prominent topic within the distributed machine learning community. Essentially, the goal is to enhance distributed optimization algorithms, such as distributed SGD, in a way that guarantees convergence despite the presence ...

PMLR2022

Adversarial Parametric Pose Prior

Pascal Fua, Mathieu Salzmann, Anastasia Remizova, Andrey Davydov, Victor Constantin, Sina Honari

The Skinned Multi-Person Linear (SMPL) model represents human bodies by mapping pose and shape parameters to body meshes. However, not all pose and shape parameter values yield physically-plausible or even realistic body meshes. In other words, SMPL is und ...

IEEE2022

Masked Training of Neural Networks with Partial Gradients

Martin Jaggi, Sebastian Urban Stich, Amirkeivan Mohtashami

State-of-the-art training algorithms for deep learning models are based on stochastic gradient descent (SGD). Recently, many variations have been explored: perturbing parameters for better accuracy (such as in Extra-gradient), limiting SGD updates to a sub ...

JMLR-JOURNAL MACHINE LEARNING RESEARCH2022

Are socially-aware trajectory prediction models really socially-aware?

Alexandre Massoud Alahi, Seyed Mohsen Moosavi Dezfooli, Saeed Saadatnejad, Mohammadhossein Bahari, Pedram Khorsandi

Our transportation field has recently witnessed an arms race of neural network-based trajectory predictors. While these predictors are at the core of many applications such as autonomous navigation or pedestrian flow simulations, their adversarial robustne ...

2022

Escaping limit cycles: Global convergence for constrained nonconvex-nonconcave minimax problems

Volkan Cevher, Thomas Michaelsen Pethick

This paper introduces a new extragradient-type algorithm for a class of nonconvex-nonconcave minimax problems. It is well-known that finding a local solution for general minimax problems is computationally intractable. This observation has recently motivat ...

2022

CryoETGAN: Cryo-Electron Tomography Image Synthesis via Unpaired Image Translation

Chengkun Li, Min Xu

Cryo-electron tomography (Cryo-ET) has been regarded as a revolution in structural biology and can reveal molecular sociology. Its unprecedented quality enables it to visualize cellular organelles and macromolecular complexes at nanometer resolution with n ...

FRONTIERS MEDIA SA2022

Simultaneous Prediction of Wrist and Hand Motions via Wearable Ultrasound Sensing for Natural Control of Hand Prostheses

Xingchen Yang

Simultaneous prediction of wrist and hand motions is essential for the natural interaction with hand prostheses. In this paper, we propose a novel multi-out Gaussian process (MOGP) model and a multi-task deep learning (MTDL) algorithm to achieve simultaneo ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2022

Synthetic Disinformation Attacks on Automated Fact Verification Systems

Antoine Bosselut

Automated fact-checking is a needed technology to curtail the spread of online misinformation. One current framework for such solutions proposes to verify claims by retrieving supporting or refuting evidence from related textual sources. However, the reali ...

ASSOC ADVANCEMENT ARTIFICIAL INTELLIGENCE2022

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Adversarial machine learning

A Methodology for Evaluating the Robustness of Anomaly Detectors to Adversarial Attacks in Industrial Scenarios

Byzantine Machine Learning Made Easy By Resilient Averaging of Momentums

Adversarial Parametric Pose Prior

Masked Training of Neural Networks with Partial Gradients

Are socially-aware trajectory prediction models really socially-aware?

Escaping limit cycles: Global convergence for constrained nonconvex-nonconcave minimax problems

Conditional Synthetic Financial Time Series with Generative Adversarial Networks

CryoETGAN: Cryo-Electron Tomography Image Synthesis via Unpaired Image Translation

Simultaneous Prediction of Wrist and Hand Motions via Wearable Ultrasound Sensing for Natural Control of Hand Prostheses

Synthetic Disinformation Attacks on Automated Fact Verification Systems

Graph Chatbot

Chat with Graph Search

Conditional Synthetic Financial Time Series with Generative Adversarial Networks

Masked Training of Neural Networks with Partial Gradients

Byzantine Machine Learning Made Easy By Resilient Averaging of Momentums

Adversarial Parametric Pose Prior

A Methodology for Evaluating the Robustness of Anomaly Detectors to Adversarial Attacks in Industrial Scenarios

Simultaneous Prediction of Wrist and Hand Motions via Wearable Ultrasound Sensing for Natural Control of Hand Prostheses

Synthetic Disinformation Attacks on Automated Fact Verification Systems

CryoETGAN: Cryo-Electron Tomography Image Synthesis via Unpaired Image Translation

Are socially-aware trajectory prediction models really socially-aware?

Escaping limit cycles: Global convergence for constrained nonconvex-nonconcave minimax problems