Search

Your search keyword '"Xiao, Jing"' showing total 30,166 results
Start Over Author "Xiao, Jing"

Refine your results

30,166 results on '"Xiao, Jing"'

101. Assessor360: Multi-sequence Network for Blind Omnidirectional Image Quality Assessment

Author

Wu, Tianhe, Shi, Shuwei, Cai, Haoming, Cao, Mingdeng, Xiao, Jing, Zheng, Yinqiang, and Yang, Yujiu

Subjects
Computer Science - Computer Vision and Pattern Recognition, Electrical Engineering and Systems Science - Image and Video Processing
Abstract

Blind Omnidirectional Image Quality Assessment (BOIQA) aims to objectively assess the human perceptual quality of omnidirectional images (ODIs) without relying on pristine-quality image information. It is becoming more significant with the increasing advancement of virtual reality (VR) technology. However, the quality assessment of ODIs is severely hampered by the fact that the existing BOIQA pipeline lacks the modeling of the observer's browsing process. To tackle this issue, we propose a novel multi-sequence network for BOIQA called Assessor360, which is derived from the realistic multi-assessor ODI quality assessment procedure. Specifically, we propose a generalized Recursive Probability Sampling (RPS) method for the BOIQA task, combining content and details information to generate multiple pseudo-viewport sequences from a given starting point. Additionally, we design a Multi-scale Feature Aggregation (MFA) module with a Distortion-aware Block (DAB) to fuse distorted and semantic features of each viewport. We also devise Temporal Modeling Module (TMM) to learn the viewport transition in the temporal domain. Extensive experimental results demonstrate that Assessor360 outperforms state-of-the-art methods on multiple OIQA datasets. The code and models are available at https://github.com/TianheWu/Assessor360.

Published
2023

102. SAR: Self-Supervised Anti-Distortion Representation for End-To-End Speech Model

Author

Wang, Jianzong, Zhang, Xulong, Tang, Haobin, Sun, Aolan, Cheng, Ning, and Xiao, Jing

Subjects
Computer Science - Sound, Electrical Engineering and Systems Science - Audio and Speech Processing
Abstract

In recent Text-to-Speech (TTS) systems, a neural vocoder often generates speech samples by solely conditioning on acoustic features predicted from an acoustic model. However, there are always distortions existing in the predicted acoustic features, compared to those of the groundtruth, especially in the common case of poor acoustic modeling due to low-quality training data. To overcome such limits, we propose a Self-supervised learning framework to learn an Anti-distortion acoustic Representation (SAR) to replace human-crafted acoustic features by introducing distortion prior to an auto-encoder pre-training process. The learned acoustic representation from the proposed framework is proved anti-distortion compared to the most commonly used mel-spectrogram through both objective and subjective evaluation., Comment: Accepted by IJCNN2023. 2023 International Joint Conference on Neural Networks (IJCNN2023)

Published
2023

103. Personalized Federated Learning via Gradient Modulation for Heterogeneous Text Summarization

Author

Pan, Rongfeng, Wang, Jianzong, Kong, Lingwei, Huang, Zhangcheng, and Xiao, Jing

Subjects
Computer Science - Artificial Intelligence
Abstract

Text summarization is essential for information aggregation and demands large amounts of training data. However, concerns about data privacy and security limit data collection and model training. To eliminate this concern, we propose a federated learning text summarization scheme, which allows users to share the global model in a cooperative learning manner without sharing raw data. Personalized federated learning (PFL) balances personalization and generalization in the process of optimizing the global model, to guide the training of local models. However, multiple local data have different distributions of semantics and context, which may cause the local model to learn deviated semantic and context information. In this paper, we propose FedSUMM, a dynamic gradient adapter to provide more appropriate local parameters for local model. Simultaneously, FedSUMM uses differential privacy to prevent parameter leakage during distributed training. Experimental evidence verifies FedSUMM can achieve faster model convergence on PFL algorithm for task-specific text summarization, and the method achieves superior performance for different optimization metrics for text summarization., Comment: Accepted by IJCNN2023. 2023 IEEE International Joint Conference on Neural Network (IJCNN2023)

Published
2023

104. Two-stage Denoising Diffusion Model for Source Localization in Graph Inverse Problems

Author

Huang, Bosong, Yu, Weihao, Xie, Ruzhong, Xiao, Jing, and Huang, Jin

Subjects
Computer Science - Machine Learning
Abstract

Source localization is the inverse problem of graph information dissemination and has broad practical applications. However, the inherent intricacy and uncertainty in information dissemination pose significant challenges, and the ill-posed nature of the source localization problem further exacerbates these challenges. Recently, deep generative models, particularly diffusion models inspired by classical non-equilibrium thermodynamics, have made significant progress. While diffusion models have proven to be powerful in solving inverse problems and producing high-quality reconstructions, applying them directly to the source localization is infeasible for two reasons. Firstly, it is impossible to calculate the posterior disseminated results on a large-scale network for iterative denoising sampling, which would incur enormous computational costs. Secondly, in the existing methods for this field, the training data itself are ill-posed (many-to-one); thus simply transferring the diffusion model would only lead to local optima. To address these challenges, we propose a two-stage optimization framework, the source localization denoising diffusion model (SL-Diff). In the coarse stage, we devise the source proximity degrees as the supervised signals to generate coarse-grained source predictions. This aims to efficiently initialize the next stage, significantly reducing its convergence time and calibrating the convergence process. Furthermore, the introduction of cascade temporal information in this training method transforms the many-to-one mapping relationship into a one-to-one relationship, perfectly addressing the ill-posed problem. In the fine stage, we design a diffusion model for the graph inverse problem that can quantify the uncertainty in the dissemination. The proposed SL-Diff yields excellent prediction results within a reasonable sampling time at extensive experiments.

Published
2023

105. Polymorphonuclear myeloid-derived suppressor cells and phosphatidylinositol-3 kinase gamma are critical to tobacco-mimicking oral carcinogenesis in mice.

Author

Nguyen, Khoa, DePledge, Lisa, Bian, Li, Ke, Yao, Samedi, Von, Berning, Amber, Owens, Philip, Wang, Xiao-Jing, and Young, Christian

Subjects
drug evaluation, preclinical, head and neck neoplasms, myeloid-derived suppressor cells, tumor microenvironment, Humans, Animals, Mice, Phosphatidylinositol 3-Kinase, Myeloid-Derived Suppressor Cells, Tobacco, Carcinoma, Squamous Cell, Mouth Neoplasms, Carcinogenesis, Carcinogens, Squamous Cell Carcinoma of Head and Neck, Head and Neck Neoplasms, Phosphatidylinositols
Abstract

BACKGROUND: Oral squamous cell carcinoma (OSCC) is a devastating disease most often associated with tobacco consumption that induces a field of mutations from which a tumor arises. Identification of ways to prevent the emergence of cancer in high-risk patients is an ultimate goal for combatting all types of cancer, including OSCC. METHODS: Our study employs a mouse model of tongue carcinogenesis induced by tobacco carcinogen mimetic, 4-nitroquinoline 1-oxide (4NQO), to establish tongue dysplasia and OSCC. We use conventional histology, immunohistochemistry, multispectral imaging, mass cytometry, novel cell lines, pharmaceutical inhibition of PI3Kγ, T-cell suppression assays and mouse transplant models in our functional experimentation. RESULTS: In our study, we identify Ly6G+ granulocytes as the most abundant immune cell type in a model of tongue carcinogenesis induced by tobacco carcinogen mimetic 4NQO. Targeting Ly6G+ granulocytes with a pharmacologic inhibitor of PI3Kγ, an isoform of PI3K exclusively expressed by myeloid cells, resulted in reduced tongue dysplasia severity, and reduced rates of OSCC. Importantly, we performed functional assays with the Ly6G+ granulocytes induced in cell line models of 4NQO carcinogenesis to demonstrate that these granulocytes have increased polymorphonuclear myeloid-derived suppressor cells (PMN-MDSC) activity against T-cell proliferation and these PMN-MDSCs play a functional role in promoting tumor formation by inhibiting tumor regression in a PI3Kγ-dependent manner. CONCLUSIONS: Overall, our data suggest that recruitment of PMN-MDSCs to sites of dysplasia is critical to immune suppression of CD8 T cells, thereby permitting malignancy, and PI3Kγ inhibitors are one mechanism to reduce PMN-MDSC recruitment, immunosuppression and tumorigenesis in OSCC.

Published
2023

106. Selective targeting of IL2Rβγ combined with radiotherapy triggers CD8- and NK-mediated immunity, abrogating metastasis in HNSCC.

Author

Gadwa, Jacob, Amann, Maria, Bickett, Thomas, Knitz, Michael, Darragh, Laurel, Piper, Miles, Van Court, Benjamin, Bukkapatnam, Sanjana, Pham, Tiffany, Wang, Xiao-Jing, Saviola, Anthony, Deak, Laura, Umaña, Pablo, Klein, Christian, DAlessandro, Angelo, and Karam, Sana

Subjects
IL-2, Tregs, cancer, head and neck cancer, immunocytokine, immunotherapy, metastasis, natural killer cells, radiation therapy, tumor immunology, Humans, Squamous Cell Carcinoma of Head and Neck, Interleukin-2, Interleukin-2 Receptor alpha Subunit, T-Lymphocytes, Cytotoxic, Head and Neck Neoplasms
Abstract

The implementation of cancer immunotherapies has seen limited clinical success in head and neck squamous cell carcinoma (HNSCC). Interleukin-2 (IL-2), which modulates the survival and functionality of lymphocytes, is an attractive target for new immunotherapies but one that is limited by presence of regulatory T cells (Tregs) expressing the high-affinity IL-2Rα. The bispecific immunocytokine PD1-IL2v preferentially delivers IL-2 signaling through IL-2Rβγ on PD-1-expressing cells. Selectively targeting the intermediate-affinity IL-2Rβγ can be leveraged to induce anti-tumor immune responses in effector T cells and natural killer (NK) cells while limiting the negative regulation of IL-2Rα activation on Tregs. Using radiation therapy (RT) in combination with PD1-IL2v improves local tumor control and survival, and controls metastatic spread in orthotopic HNSCC tumor models. PD1-IL2v drives systemic activation and expansion of circulating and tumor-infiltrating cytotoxic T cells and NK cells while limiting Treg-mediated immunosuppression. These data show that PD1-L2v induces durable systemic tumor control in HNSCC.

Published
2023

107. A global study for acute myeloid leukemia with RARG rearrangement.

Author

Zhu, Hong-Hu, Qin, Ya-Zhen, Zhang, Zhang-Lin, Liu, Yong-Jing, Wen, Li-Jun, You, M, Zhang, Cheng, Such, Esperanza, Luo, Hong, Yuan, Hong-Jian, Zhou, Hong-Sheng, Liu, Hong-Xing, Xu, Reng, Li, Ji, Li, Jian-Hu, Hao, Jian-Ping, Jin, Jie, Yu, Liang, Zhang, Jing-Ying, Liu, Li-Ping, Zhang, Le-Ping, Huang, Rui-Bin, Shen, Shu-Hong, Gao, Su-Jun, Wang, Wei, Yan, Xiao-Jing, Zhang, Xin-You, Du, Xin, Chu, Xiao-Xia, Yu, Yan-Fang, Wang, Yi, Mi, Ying-Chang, Lu, Ying, Cai, Zhen, Su, Zhan, Taussig, David, MacMahon, Suzanne, Ball, Edward, Wang, Huan-You, Welch, John, Yin, C, Borthakur, Gautam, Sanz, Miguel, Kantarjian, Hagop, Huang, Jin-Yan, Hu, Jiong, and Chen, Su-Ning

Subjects
Humans, Leukemia, Myeloid, Acute, Leukemia, Promyelocytic, Acute, Tretinoin, HLA-DR Antigens, Arsenic Trioxide
Abstract

Acute myeloid leukemia (AML) with retinoic acid receptor γ (RARG) rearrangement has clinical, morphologic, and immunophenotypic features similar to classic acute promyelocytic leukemia. However, AML with RARG rearrangement is insensitive to alltrans retinoic acid (ATRA) and arsenic trioxide (ATO) and carries a poor prognosis. We initiated a global cooperative study to define the clinicopathological features, genomic and transcriptomic landscape, and outcomes of AML with RARG rearrangements collected from 29 study groups/institutions worldwide. Thirty-four patients with AML with RARG rearrangements were identified. Bleeding or ecchymosis was present in 18 (54.5%) patients. Morphology diagnosed as M3 and M3v accounted for 73.5% and 26.5% of the cases, respectively. Immunophenotyping showed the following characteristics: positive for CD33, CD13, and MPO but negative for CD38, CD11b, CD34, and HLA-DR. Cytogenetics showed normal karyotype in 38% and t(11;12) in 26% of patients. The partner genes of RARG were diverse and included CPSF6, NUP98, HNRNPc, HNRNPm, PML, and NPM1. WT1- and NRAS/KRAS-mutations were common comutations. None of the 34 patients responded to ATRA and/or ATO. Death within 45 days from diagnosis occurred in 10 patients (∼29%). At the last follow-up, 23 patients had died, and the estimated 2-year cumulative incidence of relapse, event-free survival, and overall survival were 68.7%, 26.7%, and 33.5%, respectively. Unsupervised hierarchical clustering using RNA sequencing data from 201 patients with AML showed that 81.8% of the RARG fusion samples clustered together, suggesting a new molecular subtype. RARG rearrangement is a novel entity of AML that confers a poor prognosis. This study is registered with the Chinese Clinical Trial Registry (ChiCTR2200055810).

Published
2023

108. Harnessing the Power of Prompt Experts: Efficient Knowledge Distillation for Enhanced Language Understanding

Author

Meng, Xv, Rao, Jun, Qi, Shuhan, Wang, Lei, Xiao, Jing, Wang, Xuan, Goos, Gerhard, Series 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, Bifet, Albert, editor, Daniušis, Povilas, editor, Davis, Jesse, editor, Krilavičius, Tomas, editor, Kull, Meelis, editor, Ntoutsi, Eirini, editor, Puolamäki, Kai, editor, and Žliobaitė, Indrė, editor

Published
2024
Full Text
View/download PDF

109. Factors Influencing Investments in High-tech Start-ups: An Analysis Based on Grounded Theory

Author

Chen, Hao, Xiao, Jing, 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, Zhan, Zehui, editor, Liu, Jian, editor, Elshenawi, Dina M., editor, and Duester, Emma, editor

Published
2024
Full Text
View/download PDF

110. Prior Bilinear-Based Models for Knowledge Graph Completion

Author

Li, Jiayi, Luo, Ruilin, Sun, Jiaqi, Xiao, Jing, Yang, Yujiu, Goos, Gerhard, Series 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, Bifet, Albert, editor, Davis, Jesse, editor, Krilavičius, Tomas, editor, Kull, Meelis, editor, Ntoutsi, Eirini, editor, and Žliobaitė, Indrė, editor

Published
2024
Full Text
View/download PDF

111. Theoretical Stability Analysis of a Novel Steel–Concrete Composite Aqueduct

Author

Xiao, Jing-Lin, Nie, Jian-Guo, di Prisco, Marco, Series Editor, Chen, Sheng-Hong, Series Editor, Vayas, Ioannis, Series Editor, Kumar Shukla, Sanjay, Series Editor, Sharma, Anuj, Series Editor, Kumar, Nagesh, Series Editor, Wang, Chien Ming, Series Editor, Cui, Zhen-Dong, Series Editor, Nia, Elham Maghsoudi, editor, and Awang, Mokhtar, editor

Published
2024
Full Text
View/download PDF

112. Interventional Supervised Learning for Person Re-identification

Author

Zeng, Qingwang, Xiao, Jing, 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, Liu, Qingshan, editor, Wang, Hanzi, editor, Ma, Zhanyu, editor, Zheng, Weishi, editor, Zha, Hongbin, editor, Chen, Xilin, editor, Wang, Liang, editor, and Ji, Rongrong, editor

Published
2024
Full Text
View/download PDF

113. EdgeMA: Model Adaptation System for Real-Time Video Analytics on Edge Devices

Author

Wang, Liang, Zhang, Nan, Qu, Xiaoyang, Wang, Jianzong, Wan, Jiguang, Li, Guokuan, Hu, Kaiyu, Jiang, Guilin, Xiao, Jing, 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, Luo, Biao, editor, Cheng, Long, editor, Wu, Zheng-Guang, editor, Li, Hongyi, editor, and Li, Chaojie, editor

Published
2024
Full Text
View/download PDF

114. Innovative ASR Technology for Profile Contour and Flatness Control of Electrical Steel in Multiple-Width Schedule Free Rolling

Author

Cao, Jianguo, Song, Chunning, Wang, Leilei, Zhao, Qiufang, Xiao, Jing, Sun, Lei, Chaari, Fakher, Series Editor, Gherardini, Francesco, Series Editor, Ivanov, Vitalii, Series Editor, Haddar, Mohamed, Series Editor, Cavas-Martínez, Francisco, Editorial Board Member, di Mare, Francesca, Editorial Board Member, Kwon, Young W., Editorial Board Member, Trojanowska, Justyna, Editorial Board Member, Xu, Jinyang, Editorial Board Member, Mocellin, Katia, editor, Bouchard, Pierre-Olivier, editor, Bigot, Régis, editor, and Balan, Tudor, editor

Published
2024
Full Text
View/download PDF

115. Accuracy of cell-free Mycobacterium tuberculosis DNA testing in pleural effusion for diagnosing tuberculous pleurisy: a multicenter cross-sectional study

Author

Du, Wei-Li, Liang, Jian-Qin, Yang, Xin-Ting, Li, Cheng-Jun, Wang, Qing-Feng, Han, Wen-Ge, Li, Ye, Li, Zhi-Hui, Zhao, Dong-Mei, Xu, Fu-Dong, Rong, Yan-Xiao, Cui, Xiao-Jing, Li, Hui-Min, Wang, Feng, Liu, Peng-Chong, Guo, Dong-Lin, Wang, Hai-Bin, Xing, Xu-Ya, Che, Jia-Lu, Liu, Zi-Chen, Zhang, Na-Na, Li, Kun, Liu, Yi, Wang, Li, Wang, Hai-Bo, and Che, Nan-Ying

Published
2024
Full Text
View/download PDF

121. LILRB4 on multiple myeloma cells promotes bone lesion by p-SHP2/NF-κB/RELT signal pathway

Author

Wang, Hongying, Wang, Lei, Luan, Huiwen, Xiao, Jing, Zhao, Zhiling, Yu, Pengfei, Deng, Mi, Liu, Yifan, Ji, Shuhao, Ma, Junjie, Zhou, Yan, Zhang, Jiashen, Meng, Xianhui, Zhang, Juan, Zhao, Xinyu, Li, Chunling, Li, Fangmin, Wang, Dapeng, Wei, Shujuan, Hui, Lijun, Nie, Siman, Jin, Changzhu, An, Zhiqiang, Zhang, Ningyan, Wang, Yaopeng, Zhang, Cheng Cheng, and Li, Zunling

Published
2024
Full Text
View/download PDF

Catalog

Books, media, physical & digital resources
See catalog results