468 citations
Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
- Tsinghua UniversityCN138 papers
- University Town of ShenzhenCN25 papers
- Tsinghua Shenzhen International Graduate SchoolCN23 papers
- Chinese Academy of SciencesCN21 papers
- Tencent (China)CN13 papers
- University of California, BerkeleyUS13 papers
- Peng Cheng LaboratoryCN10 papers
- Peking UniversityCN9 papers
- Southern University of Science and TechnologyCN9 papers
- University of ManchesterGB6 papers
- École Polytechnique Fédérale de LausanneCH5 papers
- Harbin Institute of TechnologyCN5 papers
11 papers · 1 filter
SDG-L: A Semiparametric Deep Gaussian Process based Framework for Battery Capacity Prediction
Hanbing Liu, Yanru Wu, Yang Li +2
Lithium-ion batteries are becoming increasingly omnipresent in energy supply. However, the durability of energy storage using lithium-ion batteries is threatened by their dropping…
Inclusive Data Representation in Federated Learning: A Novel Approach Integrating Textual and Visual Prompt
Zihao Zhao, Zhenpeng Shi, Yang Liu +1
Federated Learning (FL) is often impeded by communication overhead issues. Prompt tuning, as a potential solution, has been introduced to only adjust a few trainable parameters rat…
HTTE: A Hybrid Technique For Travel Time Estimation In Sparse Data Environments
Nikolaos Zygouras, Nikolaos Panagiotou, Yang Li +2
Travel time estimation is a critical task, useful to many urban applications at the individual citizen and the stakeholder level. This paper presents a novel hybrid algorithm for t…
Balanced Semi-Supervised Generative Adversarial Network for Damage Assessment from Low-Data Imbalanced-Class Regime
Yuqing Gao, Pengyuan Zhai, Khalid M. Mosalam
In recent years, applying deep learning (DL) to assess structural damages has gained growing popularity in vision-based structural health monitoring (SHM). However, both data defic…
Optical Neural Ordinary Differential Equations
Yun Zhao, Hang Chen, Min Lin +5
Increasing the layer number of on-chip photonic neural networks (PNNs) is essential to improve its model performance. However, the successively cascading of network hidden layers r…
Adversarial Attack Framework on Graph Embedding Models with Limited Knowledge
Heng Chang, Yu Rong, Tingyang Xu +6
With the success of the graph embedding model in both academic and industry areas, the robustness of graph embedding against adversarial attack inevitably becomes a crucial problem…
Improving Query Efficiency of Black-box Adversarial Attack
Yang Bai, Yuyuan Zeng, Yong Jiang +3
Deep neural networks (DNNs) have demonstrated excellent performance on various tasks, however they are under the risk of adversarial examples that can be easily generated when the…
Learning Diverse and Discriminative Representations via the Principle of Maximal Coding Rate Reduction
Yaodong Yu, Kwan Ho Ryan Chan, Chong You +2
To learn intrinsic low-dimensional structures from high-dimensional data that most discriminate between classes, we propose the principle of Maximal Coding Rate Reduction ($\text{M…
Prior knowledge distillation based on financial time series
Jie Fang, Jianwu Lin
One of the major characteristics of financial time series is that they contain a large amount of non-stationary noise, which is challenging for deep neural networks. People normall…
SPI-Optimizer: an integral-Separated PI Controller for Stochastic Optimization
Dan Wang, Mengqi Ji, Yong Wang +2
To overcome the oscillation problem in the classical momentum-based optimizer, recent work associates it with the proportional-integral (PI) controller, and artificially adds D ter…
An Efficient Approach to Informative Feature Extraction from Multimodal Data
Lichen Wang, Jiaxiang Wu, Shao-Lun Huang +4
One primary focus in multimodal feature extraction is to find the representations of individual modalities that are maximally correlated. As a well-known measure of dependence, the…