Jinghui Chen

According to our database1, Jinghui Chen authored at least 52 papers between 2007 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

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In proceedings 
Article 
PhD thesis 
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Links

On csauthors.net:

Bibliography

2024
VQAttack: Transferable Adversarial Attacks on Visual Question Answering via Pre-trained Models.
CoRR, 2024

2023
Federated Learning with Projected Trajectory Regularization.
CoRR, 2023

On the Difficulty of Defending Contrastive Learning against Backdoor Attacks.
CoRR, 2023

Stealthy and Persistent Unalignment on Large Language Models via Backdoor Injections.
CoRR, 2023

VLAttack: Multimodal Adversarial Attacks on Vision-Language Tasks via Pre-trained Models.
CoRR, 2023

On the Safety of Open-Sourced Large Language Models: Does Alignment Really Prevent Them From Being Misused?
CoRR, 2023

Defending Against Alignment-Breaking Attacks via Robustly Aligned LLM.
CoRR, 2023

Defending Pre-trained Language Models as Few-shot Learners against Backdoor Attacks.
CoRR, 2023

Do Language Models Plagiarize?
Proceedings of the ACM Web Conference 2023, 2023

Benign Overfitting in Adversarially Robust Linear Classification.
Proceedings of the Uncertainty in Artificial Intelligence, 2023

A3FL: Adversarially Adaptive Backdoor Attacks to Federated Learning.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

UniT: A Unified Look at Certified Robust Training against Text Adversarial Perturbation.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Defending Pre-trained Language Models as Few-shot Learners against Backdoor Attacks.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

IMPRESS: Evaluating the Resilience of Imperceptible Perturbations Against Unauthorized Data Usage in Diffusion-Based Generative AI.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

VLATTACK: Multimodal Adversarial Attacks on Vision-Language Tasks via Pre-trained Models.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

PAT: Geometry-Aware Hard-Label Black-Box Adversarial Attacks on Text.
Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2023

Graph Contrastive Backdoor Attacks.
Proceedings of the International Conference on Machine Learning, 2023

Spectral Augmentation for Self-Supervised Learning on Graphs.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

RoCourseNet: Robust Training of a Prediction Aware Recourse Model.
Proceedings of the 32nd ACM International Conference on Information and Knowledge Management, 2023

On the Vulnerability of Backdoor Defenses for Federated Learning.
Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2022
How Powerful is Implicit Denoising in Graph Neural Networks.
CoRR, 2022

RoCourseNet: Distributionally Robust Training of a Prediction Aware Recourse Model.
CoRR, 2022

One-shot Neural Backdoor Erasing via Adversarial Weight Masking.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

LeapAttack: Hard-Label Adversarial Attack on Text via Gradient-Based Optimization.
Proceedings of the KDD '22: The 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Washington, DC, USA, August 14, 2022

Communication-Efficient Adaptive Federated Learning.
Proceedings of the International Conference on Machine Learning, 2022

Learnability Lock: Authorized Learnability Control Through Adversarial Invertible Transformations.
Proceedings of the Tenth International Conference on Learning Representations, 2022

Communication-Compressed Adaptive Gradient Method for Distributed Nonconvex Optimization.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022

Efficient Robust Training via Backward Smoothing.
Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022

2021
Evaluating and Understanding Adversarial Robustness in Deep Learning.
PhD thesis, 2021

Do Wider Neural Networks Really Help Adversarial Robustness?
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

2020
Does Network Width Really Help Adversarial Robustness?
CoRR, 2020

An Unsupervised Detection Approach for Hardware Trojans.
IEEE Access, 2020

RayS: A Ray Searching Method for Hard-label Adversarial Attack.
Proceedings of the KDD '20: The 26th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2020

Closing the Generalization Gap of Adaptive Gradient Methods in Training Deep Neural Networks.
Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence, 2020

Understanding the Intrinsic Robustness of Image Distributions using Conditional Generative Models.
Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020

A Frank-Wolfe Framework for Efficient and Effective Adversarial Attacks.
Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

2019
A machine-learning-based hardware-Trojan detection approach for chips in the Internet of Things.
Int. J. Distributed Sens. Networks, 2019

A method for indoor Wi-Fi location based on improved back propagation neural network.
Turkish J. Electr. Eng. Comput. Sci., 2019

2018
A Frank-Wolfe Framework for Efficient and Effective Adversarial Attacks.
CoRR, 2018

Closing the Generalization Gap of Adaptive Gradient Methods in Training Deep Neural Networks.
CoRR, 2018

Global Convergence of Langevin Dynamics Based Algorithms for Nonconvex Optimization.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

How do practitioners perceive assurance cases in safety-critical software systems?
Proceedings of the 11th International Workshop on Cooperative and Human Aspects of Software Engineering, 2018

Covariate Adjusted Precision Matrix Estimation via Nonconvex Optimization.
Proceedings of the 35th International Conference on Machine Learning, 2018

2017
Global Convergence of Langevin Dynamics Based Algorithms for Nonconvex Optimization.
CoRR, 2017

Robust Wirtinger Flow for Phase Retrieval with Arbitrary Corruption.
CoRR, 2017

Outlier Detection with Autoencoder Ensembles.
Proceedings of the 2017 SIAM International Conference on Data Mining, 2017

Fast Newton Hard Thresholding Pursuit for Sparsity Constrained Nonconvex Optimization.
Proceedings of the 23rd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, Halifax, NS, Canada, August 13, 2017

2016
Accelerated Stochastic Block Coordinate Gradient Descent for Sparsity Constrained Nonconvex Optimization.
Proceedings of the Thirty-Second Conference on Uncertainty in Artificial Intelligence, 2016

2015
Improved Threshold Selection by Using Calibrated Probabilities for Random Forest Classifiers.
Proceedings of the 12th Conference on Computer and Robot Vision, 2015

2012
Depth map compression via edge-based inpainting.
Proceedings of the 2012 Picture Coding Symposium, 2012

2010
The study of network layer topology discovery algorithm for optimization problem based on SNMP.
Proceedings of the International Conference on Networked Computing and Advanced Information Management, 2010

2007
Clustering Spatial Data with Obstacles Constraints by PSO.
Proceedings of the Fourth International Conference on Fuzzy Systems and Knowledge Discovery, 2007


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