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1,445 results on '"Guo, Xiaojun"'

3. Architecture Matters: Uncovering Implicit Mechanisms in Graph Contrastive Learning

Author

Guo, Xiaojun, Wang, Yifei, Wei, Zeming, and Wang, Yisen

Subjects
Computer Science - Machine Learning, Computer Science - Artificial Intelligence, Statistics - Machine Learning
Abstract

With the prosperity of contrastive learning for visual representation learning (VCL), it is also adapted to the graph domain and yields promising performance. However, through a systematic study of various graph contrastive learning (GCL) methods, we observe that some common phenomena among existing GCL methods that are quite different from the original VCL methods, including 1) positive samples are not a must for GCL; 2) negative samples are not necessary for graph classification, neither for node classification when adopting specific normalization modules; 3) data augmentations have much less influence on GCL, as simple domain-agnostic augmentations (e.g., Gaussian noise) can also attain fairly good performance. By uncovering how the implicit inductive bias of GNNs works in contrastive learning, we theoretically provide insights into the above intriguing properties of GCL. Rather than directly porting existing VCL methods to GCL, we advocate for more attention toward the unique architecture of graph learning and consider its implicit influence when designing GCL methods. Code is available at https: //github.com/PKU-ML/ArchitectureMattersGCL., Comment: NeurIPS 2023

Published
2023

6. A ferroelectric fin diode for robust non-volatile memory

Author

Feng, Guangdi, Zhu, Qiuxiang, Liu, Xuefeng, Chen, Luqiu, Zhao, Xiaoming, Liu, Jianquan, Xiong, Shaobing, Shan, Kexiang, Yang, Zhenzhong, Bao, Qinye, Yue, Fangyu, Peng, Hui, Huang, Rong, Tang, Xiaodong, Jiang, Jie, Tang, Wei, Guo, Xiaojun, Wang, Jianlu, Jiang, Anquan, Dkhil, Brahim, Tian, Bobo, Chu, Junhao, and Duan, Chungang

Published
2024
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8. ContraNorm: A Contrastive Learning Perspective on Oversmoothing and Beyond

Author

Guo, Xiaojun, Wang, Yifei, Du, Tianqi, and Wang, Yisen

Subjects
Computer Science - Machine Learning, Computer Science - Computer Vision and Pattern Recognition, Statistics - Machine Learning
Abstract

Oversmoothing is a common phenomenon in a wide range of Graph Neural Networks (GNNs) and Transformers, where performance worsens as the number of layers increases. Instead of characterizing oversmoothing from the view of complete collapse in which representations converge to a single point, we dive into a more general perspective of dimensional collapse in which representations lie in a narrow cone. Accordingly, inspired by the effectiveness of contrastive learning in preventing dimensional collapse, we propose a novel normalization layer called ContraNorm. Intuitively, ContraNorm implicitly shatters representations in the embedding space, leading to a more uniform distribution and a slighter dimensional collapse. On the theoretical analysis, we prove that ContraNorm can alleviate both complete collapse and dimensional collapse under certain conditions. Our proposed normalization layer can be easily integrated into GNNs and Transformers with negligible parameter overhead. Experiments on various real-world datasets demonstrate the effectiveness of our proposed ContraNorm. Our implementation is available at https://github.com/PKU-ML/ContraNorm., Comment: ICLR 2023

Published
2023

9. An Explicit Form with Continuous Attribute Profile of the Partial Mastery DINA Model

Author

Shu, Tian, Luo, Guanzhong, Luo, Zhaosheng, Yu, Xiaofeng, Guo, Xiaojun, and Li, Yujun

Abstract

Cognitive diagnosis models (CDMs) are the statistical framework for cognitive diagnostic assessment in education and psychology. They generally assume that subjects' latent attributes are dichotomous--mastery or nonmastery, which seems quite deterministic. As an alternative to dichotomous attribute mastery, attention is drawn to the use of a continuous attribute mastery format in recent literature. To obtain subjects' finer-grained attribute mastery for more precise diagnosis and guidance, an equivalent but more explicit form of the partial-mastery-deterministic inputs, noisy "and" gate (DINA) model (termed continuous attribute profile [CAP]-DINA form) is proposed in this article. Its parameters estimation algorithm based on this form using Bayesian techniques with Markov chain Monte Carlo algorithm is also presented. Two simulation studies are conducted then to explore its parameter recovery and model misspecification, and the results demonstrate that the CAP-DINA form performs robustly with satisfactory efficiency in these two aspects. A real data study of the English test also indicates it has a better model fit than DINA.

Published
2023
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11. Technology Roadmap for Flexible Sensors

Author

Luo, Yifei, Abidian, Mohammad Reza, Ahn, Jong-Hyun, Akinwande, Deji, Andrews, Anne M, Antonietti, Markus, Bao, Zhenan, Berggren, Magnus, Berkey, Christopher A, Bettinger, Christopher John, Chen, Jun, Chen, Peng, Cheng, Wenlong, Cheng, Xu, Choi, Seon-Jin, Chortos, Alex, Dagdeviren, Canan, Dauskardt, Reinhold H, Di, Chong-an, Dickey, Michael D, Duan, Xiangfeng, Facchetti, Antonio, Fan, Zhiyong, Fang, Yin, Feng, Jianyou, Feng, Xue, Gao, Huajian, Gao, Wei, Gong, Xiwen, Guo, Chuan Fei, Guo, Xiaojun, Hartel, Martin C, He, Zihan, Ho, John S, Hu, Youfan, Huang, Qiyao, Huang, Yu, Huo, Fengwei, Hussain, Muhammad M, Javey, Ali, Jeong, Unyong, Jiang, Chen, Jiang, Xingyu, Kang, Jiheong, Karnaushenko, Daniil, Khademhosseini, Ali, Kim, Dae-Hyeong, Kim, Il-Doo, Kireev, Dmitry, Kong, Lingxuan, Lee, Chengkuo, Lee, Nae-Eung, Lee, Pooi See, Lee, Tae-Woo, Li, Fengyu, Li, Jinxing, Liang, Cuiyuan, Lim, Chwee Teck, Lin, Yuanjing, Lipomi, Darren J, Liu, Jia, Liu, Kai, Liu, Nan, Liu, Ren, Liu, Yuxin, Liu, Yuxuan, Liu, Zhiyuan, Liu, Zhuangjian, Loh, Xian Jun, Lu, Nanshu, Lv, Zhisheng, Magdassi, Shlomo, Malliaras, George G, Matsuhisa, Naoji, Nathan, Arokia, Niu, Simiao, Pan, Jieming, Pang, Changhyun, Pei, Qibing, Peng, Huisheng, Qi, Dianpeng, Ren, Huaying, Rogers, John A, Rowe, Aaron, Schmidt, Oliver G, Sekitani, Tsuyoshi, Seo, Dae-Gyo, Shen, Guozhen, Sheng, Xing, Shi, Qiongfeng, Someya, Takao, Song, Yanlin, Stavrinidou, Eleni, Su, Meng, Sun, Xuemei, Takei, Kuniharu, Tao, Xiao-Ming, Tee, Benjamin CK, Thean, Aaron Voon-Yew, and Trung, Tran Quang

Subjects
Data Management and Data Science, Information and Computing Sciences, Humans, Wearable Electronic Devices, Quality of Life, soft materials, mechanics engineering, flexible electronics, conformable sensors, bioelectronics, human-machine interfaces, body area sensor networks, technology translation, sustainable electronics, Nanoscience & Nanotechnology
Abstract

Humans rely increasingly on sensors to address grand challenges and to improve quality of life in the era of digitalization and big data. For ubiquitous sensing, flexible sensors are developed to overcome the limitations of conventional rigid counterparts. Despite rapid advancement in bench-side research over the last decade, the market adoption of flexible sensors remains limited. To ease and to expedite their deployment, here, we identify bottlenecks hindering the maturation of flexible sensors and propose promising solutions. We first analyze challenges in achieving satisfactory sensing performance for real-world applications and then summarize issues in compatible sensor-biology interfaces, followed by brief discussions on powering and connecting sensor networks. Issues en route to commercialization and for sustainable growth of the sector are also analyzed, highlighting environmental concerns and emphasizing nontechnical issues such as business, regulatory, and ethical considerations. Additionally, we look at future intelligent flexible sensors. In proposing a comprehensive roadmap, we hope to steer research efforts towards common goals and to guide coordinated development strategies from disparate communities. Through such collaborative efforts, scientific breakthroughs can be made sooner and capitalized for the betterment of humanity.

Published
2023

17. Efficacy and safety of sovleplenib (HMPL-523) in adult patients with chronic primary immune thrombocytopenia in China (ESLIM-01): a randomised, double-blind, placebo-controlled, phase 3 study

Author

Hu, Yu, Liu, Xiaofan, Zhou, Hu, Wang, Shujie, Huang, Ruibin, Wang, Yi, Du, Xin, Sun, Jing, Zhou, Zeping, Yan, Zhenyu, Chen, Wenming, Wang, Wei, Liu, Qingchi, Zeng, Qingshu, Gong, Yuping, Yin, Jie, Shen, Xuliang, Ye, Baodong, Chen, Yun, Xu, Yajing, Sun, Huiping, Cheng, Yunfeng, Liu, Zhuogang, Wang, Chunling, Yuan, Guolin, Zhang, Xiaohui, Li, Xin, Cheng, Peng, Guo, Xinhong, Jiang, Zhongxing, Yang, Feng'e, Yang, Linhua, Luo, Chengwei, Xiao, Taiwu, Fu, Sisi, Yin, Hongyan, Guo, Xiaojun, Xu, Qian, Fan, Songhua, Shi, Michael M, Su, Weiguo, Mei, Heng, and Yang, Renchi

Published
2024
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34. Recycled Micro Surfacing Based on RAP Refined Separation Process

Author

Li, Jian, Guo, Xiaojun, Zhao, Dixia, Li, Zhihua, Wang, Peng, Wang, Jie, Zhao, Shenghui, Gao, Jieyi, Zheng, Zheng, Editor-in-Chief, Xi, Zhiyu, Associate Editor, Gong, Siqian, Series Editor, Hong, Wei-Chiang, Series Editor, Mellal, Mohamed Arezki, Series Editor, Narayanan, Ramadas, Series Editor, Nguyen, Quang Ngoc, Series Editor, Ong, Hwai Chyuan, Series Editor, Sun, Zaicheng, Series Editor, Ullah, Sharif, Series Editor, Wu, Junwei, Series Editor, Zhang, Baochang, Series Editor, Zhang, Wei, Series Editor, Zhu, Quanxin, Series Editor, Zheng, Wei, Series Editor, Ahmad, Zakiah, editor, Srivastava, Amit, editor, and Raman, Sudharshan N., editor

Published
2023
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35. Analysis on the Ideological and Political Education of Artificial Intelligence Fundamentals in the Professional Major of Unmanned Intelligence

Author

Guo, Xiaojun, Jiang, Wei, Li, Longqing, Liu, Wei, Striełkowski, Wadim, Editor-in-Chief, Black, Jessica M., Series Editor, Butterfield, Stephen A., Series Editor, Chang, Chi-Cheng, Series Editor, Cheng, Jiuqing, Series Editor, Dumanig, Francisco Perlas, Series Editor, Al-Mabuk, Radhi, Series Editor, Scheper-Hughes, Nancy, Series Editor, Urban, Mathias, Series Editor, Webb, Stephen, Series Editor, Kassim, Hafizoah, editor, Malik, Nadeem, editor, Rajagopal, Premkumar, editor, and Singh, Manjet Kaur Mehar, editor

Published
2023
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36. 'Four-in-one' Experimental Teaching Reform and Practice of Electronic Technology Basic Course

Author

Jiang, Wei, Su, Shaojing, Zuo, Zhen, Guo, Xiaojun, Shi, Meiping, Tang, Ying, Striełkowski, Wadim, Editor-in-Chief, Black, Jessica M., Series Editor, Butterfield, Stephen A., Series Editor, Chang, Chi-Cheng, Series Editor, Cheng, Jiuqing, Series Editor, Dumanig, Francisco Perlas, Series Editor, Al-Mabuk, Radhi, Series Editor, Scheper-Hughes, Nancy, Series Editor, Urban, Mathias, Series Editor, Webb, Stephen, Series Editor, Kassim, Hafizoah, editor, Malik, Nadeem, editor, Rajagopal, Premkumar, editor, and Singh, Manjet Kaur Mehar, editor

Published
2023
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37. Voxel R-CNN-MCA: Coordinate Attention for 3D Object Detection

Author

Qian, Hanxiang, Guo, Xiaojun, Sun, Xiaoyong, Su, Shaojing, Wu, Peng, Angrisani, Leopoldo, Series Editor, Arteaga, Marco, Series Editor, Panigrahi, Bijaya Ketan, Series Editor, Chakraborty, Samarjit, Series Editor, Chen, Jiming, Series Editor, Chen, Shanben, Series Editor, Chen, Tan Kay, Series Editor, Dillmann, Rüdiger, Series Editor, Duan, Haibin, Series Editor, Ferrari, Gianluigi, Series Editor, Ferre, Manuel, Series Editor, Hirche, Sandra, Series Editor, Jabbari, Faryar, Series Editor, Jia, Limin, Series Editor, Kacprzyk, Janusz, Series Editor, Khamis, Alaa, Series Editor, Kroeger, Torsten, Series Editor, Li, Yong, Series Editor, Liang, Qilian, Series Editor, Martín, Ferran, Series Editor, Ming, Tan Cher, Series Editor, Minker, Wolfgang, Series Editor, Misra, Pradeep, Series Editor, Möller, Sebastian, Series Editor, Mukhopadhyay, Subhas, Series Editor, Ning, Cun-Zheng, Series Editor, Nishida, Toyoaki, Series Editor, Oneto, Luca, Series Editor, Pascucci, Federica, Series Editor, Qin, Yong, Series Editor, Seng, Gan Woon, Series Editor, Speidel, Joachim, Series Editor, Veiga, Germano, Series Editor, Wu, Haitao, Series Editor, Zamboni, Walter, Series Editor, Zhang, Junjie James, Series Editor, Fu, Wenxing, editor, Gu, Mancang, editor, and Niu, Yifeng, editor

Published
2023
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42. Predicting Channel Quality Indicators for 5G Downlink Scheduling in a Deep Learning Approach

Author

Yin, Hao, Guo, Xiaojun, Liu, Pengyu, Hei, Xiaojun, and Gao, Yayu

Subjects
Computer Science - Networking and Internet Architecture
Abstract

5G networks provide more bandwidth and more complex control to enhance user's experiences, while also requiring a more accurate estimation of the communication channels compared with previous mobile networks. In this paper, we propose a channel quality indicator (CQI) prediction method in a deep learning approach in that a Long Short-Term Memory (LSTM) algorithm. An online training module is introduced for the downlink scheduling in the 5G New Radio (NR) system, to reduce the negative impact of outdated CQI for communication degradation, especially in high-speed mobility scenarios. First, we analyze the impact of outdated CQI in the downlink scheduling of the 5G NR system. Then, we design a data generation and online training module to evaluate our prediction method in ns-3. The simulation results show that the proposed LSTM method outperforms the Feedforward Neural Networks (FNN) method on improving the system performance of the downlink transmission. Our study may provide insights into designing new deep learning algorithms to enhance the network performance of the 5G NR system.

Published
2020

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