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3,123 results on '"Xu, Biao"'

4. Efficient Fraud Detection Using Deep Boosting Decision Trees

Author

Xu, Biao, Wang, Yao, Liao, Xiuwu, and Wang, Kaidong

Subjects
Statistics - Machine Learning, Computer Science - Machine Learning, Statistics - Applications
Abstract

Fraud detection is to identify, monitor, and prevent potentially fraudulent activities from complex data. The recent development and success in AI, especially machine learning, provides a new data-driven way to deal with fraud. From a methodological point of view, machine learning based fraud detection can be divided into two categories, i.e., conventional methods (decision tree, boosting...) and deep learning, both of which have significant limitations in terms of the lack of representation learning ability for the former and interpretability for the latter. Furthermore, due to the rarity of detected fraud cases, the associated data is usually imbalanced, which seriously degrades the performance of classification algorithms. In this paper, we propose deep boosting decision trees (DBDT), a novel approach for fraud detection based on gradient boosting and neural networks. In order to combine the advantages of both conventional methods and deep learning, we first construct soft decision tree (SDT), a decision tree structured model with neural networks as its nodes, and then ensemble SDTs using the idea of gradient boosting. In this way we embed neural networks into gradient boosting to improve its representation learning capability and meanwhile maintain the interpretability. Furthermore, aiming at the rarity of detected fraud cases, in the model training phase we propose a compositional AUC maximization approach to deal with data imbalances at algorithm level. Extensive experiments on several real-life fraud detection datasets show that DBDT can significantly improve the performance and meanwhile maintain good interpretability. Our code is available at https://github.com/freshmanXB/DBDT., Comment: 34 pages, 8 figures

Published
2023

7. Entanglement filter with Rydberg atoms

Author

Ye, Gen-Sheng, Xu, Biao, Chang, Yue, Shi, Shuai, Shi, Tao, and Li, Lin

Subjects
Physics - Atomic Physics, Quantum Physics
Abstract

Devices capable of deterministically manipulating the photonic entanglement are of paramount importance, since photons are the ideal messengers for quantum information. Here, we report a Rydberg-atom-based entanglement filter that preserves the desired photonic entangled state and deterministically blocks the transmission of the unwanted ones. Photonic entanglement with near-unity fidelity can be extracted from an input state with an arbitrarily low initial fidelity. The protocol is inherently robust, and succeeds both in the Rydberg blockade regime and in the interaction-induced dissipation regime. Such an entanglement filter opens new routes toward scalable photonic quantum information processing with multiple ensembles of Rydberg atoms., Comment: 10 pages for manuscript with 4 figures, 16 pages for Supplementary information with 7 figures and 2 tables

Published
2022
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9. Fungal diversity notes 1611–1716: taxonomic and phylogenetic contributions on fungal genera and species emphasis in south China

Author

Senanayake, Indunil C., Rossi, Walter, Leonardi, Marco, Weir, Alex, McHugh, Mark, Rajeshkumar, Kunhiraman C., Verma, Rajnish K., Karunarathna, Samantha C., Tibpromma, Saowaluck, Ashtekar, Nikhil, Ashtamoorthy, Sreejith K., Raveendran, Sanjay, Kour, Gurmeet, Singh, Aishwarya, De la Peña-Lastra, Saúl, Mateos, Antonio, Kolařík, Miroslav, Antonín, Vladimír, Ševčíková, Hana, Esteve-Raventós, Fernando, Larsson, Ellen, Pancorbo, Fermín, Moreno, Gabriel, Altés, Alberto, Turégano, Yolanda, Du, Tian-Ye, Lu, Li, Li, Qi-Rui, Kang, Ji-Chuan, Gunaseelan, Sugantha, Kezo, Kezhocuyi, Kaliyaperumal, Malarvizhi, Fu, Jizhen, Samarakoon, Milan C., Gafforov, Yusufjon, Teshaboeva, Shakhnoza, Kunjan, Pradeep C., Chamaparambath, Arya, Flakus, Adam, Etayo, Javier, Rodriguez-Flakus, Pamela, Zhurbenko, Mikhail P., de Silva, Nimali I., Tennakoon, Danushka S., Latha, K. P. Deepna, Manimohan, Patinjareveettil, Raj, K. N. Anil, Calabon, Mark S., Ahmadpour, Abdollah, Heidarian, Zeinab, Alavi, Zahra, Alavi, Fatemeh, Ghosta, Youbert, Azizi, Razmig, Luo, Mei, Zhao, Min-Ping, Kularathnage, Nuwan D., Hua, Li, Yang, Yun-Hui, Liao, Chun-Fang, Zhao, Hai-Jun, Lestari, Anis S., Jayasiri, Subashini C., Yu, Feng-Ming, Lei, Lei, Liu, Jian-Wei, Karimi, Omid, Tang, Song-Ming, Sun, Ya-Ru, Wang, Yong, Zeng, Ming, Htet, Zin H., Linaldeddu, Benedetto T., Alves, Artur, Phillips, Alan J. L., Bregant, Carlo, Montecchio, Lucio, De Kesel, André, Hustad, Vincent P., Miller, Andrew N., Fedosova, Anna G., Kučera, Viktor, Raza, Mubashar, Hussain, Muzammil, Chen, Yan-Peng, Thiyagaraja, Vinodhini, Gomdola, Deecksha, Rathnayaka, Achala R., Dissanayake, Asha J., Suwannarach, Nakarin, Hongsanan, Sinang, Maharachchikumbura, Sajeewa S. N., Dissanayake, Lakmali S., Wijayawardene, Nalin N., Phookamsak, Rungtiwa, Lumyong, Saisamorn, Jones, E. B. Gareth, Yapa, Neelamanie, Wanasinghe, Dhanushka N., Xie, Ning, Doilom, Mingkwan, Manawasinghe, Ishara S., Liu, Jian-Kui (Jack), Zhao, Qi, Xu, Biao, Hyde, Kevin D., and Song, Jiage

Published
2023
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30. Conflict-free Cooperation Method for Connected and Automated Vehicles at Unsignalized Intersections: Graph-based Modeling and Optimality Analysis

Author

Chen, Chaoyi, Xu, Qing, Cai, Mengchi, Wang, Jiawei, Wang, Jianqiang, Xu, Biao, and Li, Keqiang

Subjects
Computer Science - Robotics, Electrical Engineering and Systems Science - Systems and Control
Abstract

Connected and automated vehicles have shown great potential in improving traffic mobility and reducing emissions, especially at unsignalized intersections. Previous research has shown that vehicle passing order is the key influencing factor in improving intersection traffic mobility. In this paper, we propose a graph-based cooperation method to formalize the conflict-free scheduling problem at an unsignalized intersection. Based on graphical analysis, a vehicle's trajectory conflict relationship is modeled as a conflict directed graph and a coexisting undirected graph. Then, two graph-based methods are proposed to find the vehicle passing order. The first is an improved depth-first spanning tree algorithm, which aims to find the local optimal passing order vehicle by vehicle. The other novel method is a minimum clique cover algorithm, which identifies the global optimal solution. Finally, a distributed control framework and communication topology are presented to realize the conflict-free cooperation of vehicles. Extensive numerical simulations are conducted for various numbers of vehicles and traffic volumes, and the simulation results prove the effectiveness of the proposed algorithms.

Published
2021

38. A Graph-based Conflict-free Cooperation Method for Intelligent Electric Vehicles at Unsignalized Intersections

Author

Chen, Chaoyi, Xu, Qing, Cai, Mengchi, Wang, Jiawei, Xu, Biao, Wu, Xiangbin, Wang, Jianqiang, Li, Keqiang, and Qi, Chunyu

Subjects
Mathematics - Optimization and Control
Abstract

Electric, intelligent, and network are the most important future development directions of automobiles. Intelligent electric vehicles have shown great potentials to improve traffic mobility and reduce emissions, especially at unsignalized intersections. Previous research has shown that vehicle passing order is the key factor in traffic mobility improvement. In this paper, we propose a graph-based cooperation method to formalize the conflict-free scheduling problem at unsignalized intersections. Firstly, conflict directed graphs and coexisting undirected graphs are built to describe the conflict relationship of the vehicles. Then, two graph-based methods are introduced to solve the vehicle passing order. One method is an optimized depth-first spanning tree method which aims to find the local optimal passing order for each vehicle. The other method is a maximum matching algorithm that solves the global optimal problem. The computational complexity of both methods is also derived. Numerical simulation results demonstrate the effectiveness of the proposed algorithms.

Published
2021

39. MOSI APP - A Motion Cueing Application to Mitigate Car Sickness While Performing Non-driving Task

Author

Li, Daofei, Xu, Biao, Chen, Linhui, Tang, Binbin, Yu, Tingzhe, Zhou, Keyuan, Qie, Nan, Shi, Yilei, Lu, Cheng, Zhang, Haimo, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Yung, Moti, Editorial Board Member, and Krömker, Heidi, editor

Published
2023
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41. Hypersonic Vehicle Tracking Algorithm Based on Virtual Radar Constructed by Artificial Intelligence

Author

Xu, Biao, Zhu, Xuxin, Li, Shuang, Zhang, Jinpeng, 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, Yan, Liang, editor, and Deng, Yimin, editor

Published
2023
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42. A study on group difference between low-carbon transportation intention and consistent behavior(考虑群体差异的低碳出行意向与行为一致性研究)

Author

徐标(XU Biao)

Subjects
Electronic computers. Computer science, QA75.5-76.95, Physics, QC1-999
Abstract

为探究城市居民低碳出行意向与行为差异的原因和异质性，基于大中小城市、老中青群体1 263名居民的低碳出行问卷调查数据，采用双变量Probit模型和组间平均边际效应（AME），分析了城市和群体间低碳出行意向与行为一致性的影响因素及群体差异。结果表明：有低碳出行意向与行为的居民比例仅为12.6%，有低碳出行意向而未向行为转变的居民占55.3%，意向与行为不一致的现象在一线城市和青年群体中尤为明显。从平均边际效应的结果看，有无私家车是导致一线、二线城市居民和中、青年群体低碳出行意向与行为不一致的关键因素。环境意识和主观规范对老年群体的低碳出行意向与行为一致性具有更显著的积极影响。研究所揭示的影响不同群体低碳出行意向与行为一致性的关键因素，可为低碳政策的异质化实施提供理论参考。

Published
2023
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49. Magnifying image-enhanced endoscopy–only mode boosted early cancer diagnostic efficiency: a multicenter randomized controlled trial

Author

Jiang, Ai-Rui, Wen, Li-Ming, Ding, Jian-Wei, Zou, Rui-Zheng, Nie, Xu-Biao, Lin, Hui, Chen, Jing, Zhang, Wei-Sen, Dan, Liang-Ying, Zhu, Yu-Xia, Ren, Chun-Mei, Wu, Ying-Yang, Sheng, Lin-Lin, Chen, Ding-Rong, Liao, Guo-Bin, Zhao, Hai-Yan, Li, Jian-Jun, Zuo, Ying, Chen, Jie, Bai, Jian-Ying, Xu, Liang-Bi, and Yu, Shuang

Published
2023
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