Chenhao Ye — accepted AI-conference papers

2026

Depth-Progressive Monotonic Learning without Backpropagation

Chenhao Ye, Rongguang Ye, Yuchao Zhang, Ming Tang

ICML 2026poster

Backpropagation (BP) remains the dominant training paradigm for deep neural networks, yet its reliance on global gradient propagation fundamentally induces update locking problem, enforcing strong inter-layer dependencies in parameter updates. To address this limitation, we propose Depth-progressive…

Cited by 0 Source ↗Scholar ↗

2025

Distill To Detect: Amplifying Anomalies in Backdoor Models through Knowledge Distillation

Chang Hu, Xuyang Teng, Wenpeng Xing, Han Chen, Chenhao Ye, Meng Han

ICASSP 2025accepted

Backdoor attacks represent a significant threat to the security of deep learning models. Due to the stealthiness of backdoor attacks, effectively detecting whether a model has been compromised by such attacks remains a major challenge. Previous backdoor detection methods either rely on backdoor data…

Cited by 0 Source ↗Scholar ↗