14 citations · 34 across the 11 of their papers we have counts for
4 papers · 1 filter
GALOT: Generative Active Learning via Optimizable Zero-shot Text-to-image Generation
Hanbin Hong, Shenao Yan, Shuya Feng +2
Active Learning (AL) represents a crucial methodology within machine learning, emphasizing the identification and utilization of the most informative samples for efficient model tr…
Universally Harmonizing Differential Privacy Mechanisms for Federated Learning: Boosting Accuracy and Convergence
Shuya Feng, Meisam Mohammady, Hanbin Hong +4
Differentially private federated learning (DP-FL) is a promising technique for collaborative model training while ensuring provable privacy for clients. However, optimizing the tra…
An LLM-Assisted Easy-to-Trigger Backdoor Attack on Code Completion Models: Injecting Disguised Vulnerabilities against Strong Detection
Shenao Yan, Shen Wang, Yue Duan +4
Large Language Models (LLMs) have transformed code completion tasks, providing context-based suggestions to boost developer productivity in software engineering. As users often fin…
Certifying Adapters: Enabling and Enhancing the Certification of Classifier Adversarial Robustness
Jieren Deng, Hanbin Hong, Aaron Palmer +5
Randomized smoothing has become a leading method for achieving certified robustness in deep classifiers against l_{p}-norm adversarial perturbations. Current approaches for achievi…