Han Hu

GCNet: Non-Local Networks Meet Squeeze-Excitation Networks and Beyond

2019

The Non-Local Network (NLNet) presents a pioneering approach for capturing long-range dependencies, via aggregating query-specific global context to each query position. However, through a rigorous empirical analysis, we have found that the global contexts modeled …

Aligning Pretraining for Detection via Object-Level Contrastive Learning

2021 · arXiv (Cornell University)

Image-level contrastive representation learning has proven to be highly effective as a generic model for transfer learning. Such generality for transfer learning, however, sacrifices specificity if we are interested in a certain downstream task. We …

Optimizing Data Center Energy Efficiency via Event-Driven Deep Reinforcement Learning

2022 · IEEE Transactions on Services Computing

To reduce the skyrocketing energy consumption of data centers, the prevailing approaches adopt the time-driven manner to control IT and cooling subsystems. These methods suffer from highly dynamic system states, complex action spaces and the …

Carrier Frequency Offset in Internet of Things Radio Frequency Fingerprint Identification: An Experimental Review

2023 · IEEE Internet of Things Journal

Radio frequency fingerprint (RFF) identification has become a promising security solution for resource-constrained Internet-of-Things (IoT) devices, which relies on hardware impairments-induced radio frequency features for identification; among which, a hotspot feature is the carrier frequency …

Joint Input and Output Coordination for Class-Incremental Learning

2024 · arXiv (Cornell University)

Incremental learning is nontrivial due to severe catastrophic forgetting. Although storing a small amount of data on old tasks during incremental learning is a feasible solution, current strategies still do not 1) adequately address the …

Hypergraph Foundation Model

2025 · IEEE Transactions on Pattern Analysis and Machine Intelligence

Hypergraph neural networks (HGNNs) effectively model complex high-order relationships in domains like protein interactions and social networks by connecting multiple vertices through hyperedges, enhancing modeling capabilities, and reducing information loss. Developing foundation models for hypergraphs …