no code implementations • 13 May 2024 • Hanyan Yin, Dongxie Wen, Jiajun Li, Zhewei Wei, Xiao Zhang, Zengfeng Huang, Feifei Li
Matrix sketching, aimed at approximating a matrix $\boldsymbol{A} \in \mathbb{R}^{N\times d}$ consisting of vector streams of length $N$ with a smaller sketching matrix $\boldsymbol{B} \in \mathbb{R}^{\ell\times d}, \ell \ll N$, has garnered increasing attention in fields such as large-scale data analytics and machine learning.
no code implementations • 9 May 2024 • Feifei Li, Suhan Guo, Feng Han, Jian Zhao, Furao Shen
Accurate forecasting of long-term time series has important applications for decision making and planning.
no code implementations • 17 Apr 2024 • Chi Zhang, Qi Song, Feifei Li, Yongquan Chen, Rui Huang
Constructing vectorized high-definition maps from surround-view cameras has garnered significant attention in recent years.
no code implementations • 9 Jan 2024 • Jun Ma, Feifei Li, Bo wang
Convolutional Neural Networks (CNNs) and Transformers have been the most popular architectures for biomedical image segmentation, but both of them have limited ability to handle long-range dependencies because of inherent locality or computational complexity.
1 code implementation • 7 Jul 2023 • Ling Chen, Chaodu Song, Xu Wang, Dachao Fu, Feifei Li
To this end, we propose CSCLog, a Component Subsequence Correlation-Aware Log anomaly detection method, which not only captures the sequential dependencies in subsequences, but also models the implicit correlations of subsequences.
no code implementations • 5 Jul 2023 • Jiaqi Wang, Tianyi Li, Anni Wang, Xiaoze Liu, Lu Chen, Jie Chen, Jianye Liu, Junyang Wu, Feifei Li, Yunjun Gao
This has led to the increasing volume of database workloads, which provides the opportunity for pattern analysis.
2 code implementations • 24 Apr 2023 • Jun Ma, Yuting He, Feifei Li, Lin Han, Chenyu You, Bo wang
Medical image segmentation is a critical component in clinical practice, facilitating accurate diagnosis, treatment planning, and disease monitoring.
1 code implementation • 4 Apr 2023 • Xiao He, Ye Li, Jian Tan, Bin Wu, Feifei Li
Extensive experiments on real-world benchmark datasets for downstream time series anomaly detection and forecasting tasks demonstrate that OneShotSTL is from 10 to over 1, 000 times faster than the state-of-the-art methods, while still providing comparable or even better accuracy.
no code implementations • 10 Mar 2023 • Xinyi Zhang, Zhuo Chang, Hong Wu, Yang Li, Jia Chen, Jian Tan, Feifei Li, Bin Cui
To tune different components for DBMS, a coordinating mechanism is needed to make the multiple agents cognizant of each other.
no code implementations • 21 Feb 2023 • Dayong Tian, Feifei Li, Yiwen Wei
We also propose a loss function to measure the similarities between binary labels in datasets and interval type-2 fuzzy memberships generated by our model.
3 code implementations • 13 Dec 2022 • Zhe Zhao, Yudong Li, Cheng Hou, Jing Zhao, Rong Tian, Weijie Liu, Yiren Chen, Ningyuan Sun, Haoyan Liu, Weiquan Mao, Han Guo, Weigang Guo, Taiqiang Wu, Tao Zhu, Wenhang Shi, Chen Chen, Shan Huang, Sihong Chen, Liqun Liu, Feifei Li, Xiaoshuai Chen, Xingwu Sun, Zhanhui Kang, Xiaoyong Du, Linlin Shen, Kimmo Yan
The proposed pre-training models of different modalities are showing a rising trend of homogeneity in their model structures, which brings the opportunity to implement different pre-training models within a uniform framework.
no code implementations • 5 May 2022 • Zhi Qi, Hong Xie, Ye Li, Jian Tan, Feifei Li, John C. S. Lui
LPC-AD is motivated by the ever-increasing needs for fast and accurate MTS anomaly detection methods to support fast troubleshooting in cloud computing, micro-service systems, etc.
no code implementations • 18 Oct 2021 • Jiahui Geng, Yongli Mou, Feifei Li, Qing Li, Oya Beyan, Stefan Decker, Chunming Rong
We find that image restoration fails even if there is only one incorrectly inferred label in the batch; we also find that when batch images have the same label, the corresponding image is restored as a fusion of that class of images.
3 code implementations • 26 May 2021 • Debjyoti Paul, Jie Cao, Feifei Li, Vivek Srikumar
To address this workload characterization problem, we propose our query plan encoders that learn essential features and their correlations from query plans.
no code implementations • 13 Oct 2019 • Yuwei Wang, Yan Zheng, Yanqing Peng, Chin-Chia Michael Yeh, Zhongfang Zhuang, Das Mahashweta, Bendre Mangesh, Feifei Li, Wei zhang, Jeff M. Phillips
Embeddings are already essential tools for large language models and image analysis, and their use is being extended to many other research domains.