no code implementations • 24 Dec 2024 • Yuhan Zhao, Rui Chen, Li Chen, Shuang Zhang, Qilong Han, Hongtao Song
However, bridging the gap in practice encounters two formidable challenges: (1) none of the real-world datasets contains full ranking information; (2) there does not exist a loss function that is capable of consuming ranking information.
1 code implementation • 24 Dec 2024 • Yuhan Zhao, Rui Chen, Qilong Han, Hongtao Song, Li Chen
Implementing the PNN paradigm is, however, technically challenging because: (1) it is difficult to classify unlabeled data into neutral or negative in the absence of supervised signals; (2) there does not exist any loss function that can handle set-level triple-wise ranking relationships.
1 code implementation • 14 Dec 2024 • Jiaxu Li, Songning Lai, Rui Li, Di Fang, Kejia Fan, Jianheng Tang, Yuhan Zhao, Rongchang Zhao, Dongzhan Zhou, Yutao Yue, Huiping Zhuang
Extensive experiments on the Pascal VOC2012 dataset show that SegACIL achieves superior performance in the sequential, disjoint, and overlap settings, offering a robust solution to the challenges of class-incremental semantic segmentation.
1 code implementation • 4 Nov 2024 • Anran Zhang, Xingfen Wang, Yuhan Zhao
While previous research has effectively leveraged network topology and attribute information for attributed community detection, these methods overlook two critical issues: (i) the semantic similarity between node attributes within the community, and (ii) the inherent mesoscopic structure, which differs from the pairwise connections of the micro-structure.
no code implementations • 4 Jul 2024 • Huanzhang Dou, Pengyi Zhang, Yuhan Zhao, Lu Jin, Xi Li
To enhance the sensitivity to the walking pattern while maintaining the robustness of recognition, we present a Complementary Learning with neural Architecture Search (CLASH) framework, consisting of walking pattern sensitive gait descriptor named dense spatial-temporal field (DSTF) and neural architecture search based complementary learning (NCL).
no code implementations • 3 Jan 2024 • Yuhan Zhao, Juntao Chen, Quanyan Zhu
The attacker aims to exploit this vulnerability to enable a successful physical compromise, while the system operator's goal is to ensure a normal operation of the grid by mitigating cyber risks.
1 code implementation • 26 Oct 2023 • Weixin Chen, Li Chen, Yongxin Ni, Yuhan Zhao
Recently, multimodal recommendations (MMR) have gained increasing attention for alleviating the data sparsity problem of traditional recommender systems by incorporating modality-based representations.
1 code implementation • 11 Aug 2023 • Yuhan Zhao, Rui Chen, Riwei Lai, Qilong Han, Hongtao Song, Li Chen
To balance efficiency and effectiveness, the vast majority of existing methods follow the two-pass approach, in which the first pass samples a fixed number of unobserved items by a simple static distribution and then the second pass selects the final negative items using a more sophisticated negative sampling strategy.
no code implementations • 6 Jun 2023 • Huanzhang Dou, Pengyi Zhang, Yuhan Zhao, Lin Dong, Zequn Qin, Xi Li
In this work, we propose to solve the hard sample issue with a Memory-augmented Progressive Learning network (GaitMPL), including Dynamic Reweighting Progressive Learning module (DRPL) and Global Structure-Aligned Memory bank (GSAM).
no code implementations • 11 Nov 2022 • Yuhan Zhao, Quanyan Zhu
To this end, we develop a meta-learning-based Stackelberg game-theoretic framework to address the challenges in the guided cooperative control for linear systems.
no code implementations • 9 Aug 2022 • Yuhan Zhao, Craig Rieger, Quanyan Zhu
In this book chapter, we present a multi-agent system (MAS) framework for distributed large-scale control systems and discuss the role of MAS learning in resiliency.
no code implementations • 3 Mar 2022 • Yuhan Zhao, Quanyan Zhu
As on-orbit repairs are challenging, a distributed and autonomous protection mechanism is necessary to ensure the adaptation and self-healing of the satellite constellation coverage from different attacks.
no code implementations • 30 May 2021 • Pengyi Zhang, Huanzhang Dou, Wenhu Zhang, Yuhan Zhao, Songyuan Li, Zequn Qin, Xi Li
To diversify the extrinsic factors of gait, we build a complicated scene with a dense camera layout.
no code implementations • 5 Jan 2021 • Huanzhang Dou, Wenhu Zhang, Pengyi Zhang, Yuhan Zhao, Songyuan Li, Zequn Qin, Fei Wu, Lin Dong, Xi Li
With the motivation of practical gait recognition applications, we propose to automatically create a large-scale synthetic gait dataset (called VersatileGait) by a game engine, which consists of around one million silhouette sequences of 11, 000 subjects with fine-grained attributes in various complicated scenarios.