Sanghyun Hong

Orcid: 0000-0003-4154-7611

Affiliations:

Oregon State University, Corvallis, OR, USA
University of Maryland, College Park, MD, USA (PhD 2021)

According to our database¹, Sanghyun Hong authored at least 41 papers between 2017 and 2024.

Collaborative distances:

Dijkstra number² of four.
Erdős number³ of four.

Timeline

Legend:

Book

In proceedings

Article

PhD thesis

Dataset

Other

Bibliography

2024

Visualizationary: Automating Design Feedback for Visualization Designers using LLMs.

[BibT_eX]

[DOI]

Sungbok Shin

Sanghyun Hong

Niklas Elmqvist

CoRR, 2024

Hard Work Does Not Always Pay Off: Poisoning Attacks on Neural Architecture Search.

[BibT_eX]

[DOI]

CoRR, 2024

Privacy Backdoors: Enhancing Membership Inference through Poisoning Pre-trained Models.

[BibT_eX]

[DOI]

CoRR, 2024

Diffusion Denoising as a Certified Defense against Clean-label Poisoning.

[BibT_eX]

[DOI]

Sanghyun Hong

Nicholas Carlini

Alexey Kurakin

CoRR, 2024

Parameterized Physics-informed Neural Networks for Parameterized PDEs.

[BibT_eX]

[DOI]

Proceedings of the Forty-first International Conference on Machine Learning, 2024

LeaPformer: Enabling Linear Transformers for Autoregressive and Simultaneous Tasks via Learned Proportions.

[BibT_eX]

[DOI]

Victor Agostinelli

Sanghyun Hong

Lizhong Chen

Proceedings of the Forty-first International Conference on Machine Learning, 2024

PAC-FNO: Parallel-Structured All-Component Fourier Neural Operators for Recognizing Low-Quality Images.

[BibT_eX]

[DOI]

Proceedings of the Twelfth International Conference on Learning Representations, 2024

Message from the DSML Workshop Chairs; DSN-W 2024.

[BibT_eX]

[DOI]

Sanghyun Hong

Bo Fang

Proceedings of the 54th Annual IEEE/IFIP International Conference on Dependable Systems and Networks, 2024

When Do "More Contexts" Help with Sarcasm Recognition?

[BibT_eX]

[DOI]

Ojas Nimase

Sanghyun Hong

Proceedings of the 2024 Joint International Conference on Computational Linguistics, 2024

Identifying Contemporaneous and Lagged Dependence Structures by Promoting Sparsity in Continuous-time Neural Networks.

[BibT_eX]

[DOI]

Proceedings of the 33rd ACM International Conference on Information and Knowledge Management, 2024

Operator-Learning-Inspired Modeling of Neural Ordinary Differential Equations.

[BibT_eX]

[DOI]

Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023

A Scanner Deeply: Predicting Gaze Heatmaps on Visualizations Using Crowdsourced Eye Movement Data.

[BibT_eX]

[DOI]

IEEE Trans. Vis. Comput. Graph., 2023

Perceptual Pat: A Virtual Human System for Iterative Visualization Design.

[BibT_eX]

[DOI]

Sungbok Shin

Sanghyun Hong

Niklas Elmqvist

CoRR, 2023

Publishing Efficient On-device Models Increases Adversarial Vulnerability.

[BibT_eX]

[DOI]

Sanghyun Hong

Nicholas Carlini

Alexey Kurakin

Proceedings of the 2023 IEEE Conference on Secure and Trustworthy Machine Learning, 2023

BERT Lost Patience Won't Be Robust to Adversarial Slowdown.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Learning Unforeseen Robustness from Out-of-distribution Data Using Equivariant Domain Translator.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Machine Learning, 2023

Perceptual Pat: A Virtual Human Visual System for Iterative Visualization Design.

[BibT_eX]

[DOI]

Sungbok Shin

Sanghyun Hong

Niklas Elmqvist

Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems, 2023

2022

Time Series Forecasting with Hypernetworks Generating Parameters in Advance.

[BibT_eX]

[DOI]

CoRR, 2022

Mining Causality from Continuous-time Dynamics Models: An Application to Tsunami Forecasting.

[BibT_eX]

[DOI]

CoRR, 2022

AdamNODEs: When Neural ODE Meets Adaptive Moment Estimation.

[BibT_eX]

[DOI]

CoRR, 2022

Handcrafted Backdoors in Deep Neural Networks.

[BibT_eX]

[DOI]

Sanghyun Hong

Nicholas Carlini

Alexey Kurakin

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Improving cross-platform binary analysis using representation learning via graph alignment.

[BibT_eX]

[DOI]

Proceedings of the ISSTA '22: 31st ACM SIGSOFT International Symposium on Software Testing and Analysis, Virtual Event, South Korea, July 18, 2022

Data Poisoning Won't Save You From Facial Recognition.

[BibT_eX]

[DOI]

Proceedings of the Tenth International Conference on Learning Representations, 2022

Truth Serum: Poisoning Machine Learning Models to Reveal Their Secrets.

[BibT_eX]

[DOI]

Proceedings of the 2022 ACM SIGSAC Conference on Computer and Communications Security, 2022

2021

Building Secure and Reliable Deep Learning Systems from a Systems Security Perspective.

[BibT_eX]

[DOI]

Sanghyun Hong

PhD thesis, 2021

Qu-ANTI-zation: Exploiting Quantization Artifacts for Achieving Adversarial Outcomes.

[BibT_eX]

[DOI]

Sanghyun Hong

Michael-Andrei Panaitescu-Liess

Yigitcan Kaya

Tudor Dumitras

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

A Panda? No, It's a Sloth: Slowdown Attacks on Adaptive Multi-Exit Neural Network Inference.

[BibT_eX]

[DOI]

Proceedings of the 9th International Conference on Learning Representations, 2021

Certified Malware in South Korea: A Localized Study of Breaches of Trust in Code-Signing PKI Ecosystem.

[BibT_eX]

[DOI]

Proceedings of the Information and Communications Security - 23rd International Conference, 2021

2020

On the Effectiveness of Regularization Against Membership Inference Attacks.

[BibT_eX]

[DOI]

Yigitcan Kaya

Sanghyun Hong

Tudor Dumitras

CoRR, 2020

On the Effectiveness of Mitigating Data Poisoning Attacks with Gradient Shaping.

[BibT_eX]

[DOI]

CoRR, 2020

How to 0wn the NAS in Your Spare Time.

[BibT_eX]

[DOI]

Proceedings of the 8th International Conference on Learning Representations, 2020

2019

Poster: On the Feasibility of Training Neural Networks with Visibly Watermarked Dataset.

[BibT_eX]

[DOI]

CoRR, 2019

Terminal Brain Damage: Exposing the Graceless Degradation in Deep Neural Networks Under Hardware Fault Attacks.

[BibT_eX]

[DOI]

Proceedings of the 28th USENIX Security Symposium, 2019

Shallow-Deep Networks: Understanding and Mitigating Network Overthinking.

[BibT_eX]

[DOI]

Yigitcan Kaya

Sanghyun Hong

Tudor Dumitras

Proceedings of the 36th International Conference on Machine Learning, 2019

2018

Security Analysis of Deep Neural Networks Operating in the Presence of Cache Side-Channel Attacks.

[BibT_eX]

[DOI]

CoRR, 2018

Peek-a-boo: Inferring program behaviors in a virtualized infrastructure without introspection.

[BibT_eX]

[DOI]

Comput. Secur., 2018

On Integrating Knowledge Graph Embedding into SPARQL Query Processing.

[BibT_eX]

[DOI]

Proceedings of the 2018 IEEE International Conference on Web Services, 2018

Go Serverless: Securing Cloud via Serverless Design Patterns.

[BibT_eX]

[DOI]

Proceedings of the 10th USENIX Workshop on Hot Topics in Cloud Computing, 2018

PAGE: Answering Graph Pattern Queries via Knowledge Graph Embedding.

[BibT_eX]

[DOI]

Proceedings of the Big Data - BigData 2018, 2018

2017

Summoning Demons: The Pursuit of Exploitable Bugs in Machine Learning.

[BibT_eX]

[DOI]

CoRR, 2017

SENA: Preserving Social Structure for Network Embedding.

[BibT_eX]

[DOI]

Proceedings of the 28th ACM Conference on Hypertext and Social Media, 2017

Sanghyun Hong

Timeline

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