1 code implementation • 1 Dec 2022 • Fangye Wang, Yingxu Wang, Dongsheng Li, Hansu Gu, Tun Lu, Peng Zhang, Ning Gu
Many Click-Through Rate (CTR) prediction works focused on designing advanced architectures to model complex feature interactions but neglected the importance of feature representation learning, e. g., adopting a plain embedding layer for each feature, which results in sub-optimal feature representations and thus inferior CTR prediction performance.
1 code implementation • 19 Apr 2022 • Fangye Wang, Yingxu Wang, Dongsheng Li, Hansu Gu, Tun Lu, Peng Zhang, Ning Gu
However, most methods only learn a fixed representation for each feature without considering the varying importance of each feature under different contexts, resulting in inferior performance.
no code implementations • 9 Aug 2021 • Mohammad Salimibeni, Zohreh Hajiakhondi-Meybodi, Arash Mohammadi, Yingxu Wang
Recently, as a consequence of the COVID-19 pandemic, dependence on Contact Tracing (CT) models has significantly increased to prevent spread of this highly contagious virus and be prepared for the potential future ones.
no code implementations • 11 Feb 2021 • Yingxu Wang, Fakhri Karray, Sam Kwong, Konstantinos N. Plataniotis, Henry Leung, Ming Hou, Edward Tunstel, Imre J. Rudas, Ljiljana Trajkovic, Okyay Kaynak, Janusz Kacprzyk, Mengchu Zhou, Michael H. Smith, Philip Chen, Shushma Patel
Symbiotic Autonomous Systems (SAS) are advanced intelligent and cognitive systems exhibiting autonomous collective intelligence enabled by coherent symbiosis of human-machine interactions in hybrid societies.
no code implementations • 28 Dec 2020 • Arash Mohammadi, Yingxu Wang, Nastaran Enshaei, Parnian Afshar, Farnoosh Naderkhani, Anastasia Oikonomou, Moezedin Javad Rafiee, Helder C. R. Oliveira, Svetlana Yanushkevich, Konstantinos N. Plataniotis
This has resulted in a surge of interest to develop Radiomics models for analysis and interpretation of medical images.
no code implementations • 28 Feb 2019 • Yingcheng Su, Shunfeng Zhou, Yi-Chao Wu, Tian Su, Ding Liang, Jiaheng Liu, Dixin Zheng, Yingxu Wang, Junjie Yan, Xiaolin Hu
Although deeper and larger neural networks have achieved better performance, the complex network structure and increasing computational cost cannot meet the demands of many resource-constrained applications.