Hang Su
8 papers in the PaperMetrix corpus
Papers by this author
-
Forecast the Plausible Paths in Crowd Scenes
2017
Forecasting the future plausible paths of pedestrians in crowd scenes is of wide applications, but it still remains as a challenging task due to the complexities and uncertainties of crowd motions. To address these issues, …
-
Sparse Adversarial Perturbations for Videos
2018 · arXiv (Cornell University)
Although adversarial samples of deep neural networks (DNNs) have been intensively studied on static images, their extensions in videos are never explored. Compared with images, attacking a video needs to consider not only spatial cues …
-
Reward Shaping via Meta-Learning
2019 · arXiv (Cornell University)
Reward shaping is one of the most effective methods to tackle the crucial yet challenging problem of credit assignment in Reinforcement Learning (RL). However, designing shaping functions usually requires much expert knowledge and hand-engineering, and …
-
Benchmarking Adversarial Robustness
2019 · arXiv (Cornell University)
Deep neural networks are vulnerable to adversarial examples, which becomes one of the most important research problems in the development of deep learning. While a lot of efforts have been made in recent years, it …
-
Triple-Memory Networks: A Brain-Inspired Method for Continual Learning
2021 · IEEE Transactions on Neural Networks and Learning Systems
Continual acquisition of novel experience without interfering with previously learned knowledge, i.e., continual learning, is critical for artificial neural networks, while limited by catastrophic forgetting. A neural network adjusts its parameters when learning a new …
-
Energy Efficient Offloading Mechanism for Blocks in Blockchain-Assist IoT System
2023
With the development and large-scale application of the Internet of Things (IoT), security issues in IoT systems have received widespread attention. Applying blockchain technology can effectively solve the security risks faced by IoT systems. However, …
-
Membership Inference on Text-to-Image Diffusion Models via Conditional Likelihood Discrepancy
2024 · arXiv (Cornell University)
Text-to-image diffusion models have achieved tremendous success in the field of controllable image generation, while also coming along with issues of privacy leakage and data copyrights. Membership inference arises in these contexts as a potential …
-
A Novel Data-Driven Visualization and Analysis Framework for Embedded Robotic Firmware
2025
The growing complexity of embedded firmware in robotics and automation, including mobile robots, industrial actuators, and autonomous systems, presents significant challenges related to maintainability, debugging, and efficient developer onboarding. Traditional documentation methods frequently become outdated …