Search Results - "Hou, Zhaoxiang"

DFML: Dynamic Federated Meta-Learning for Rare Disease Prediction by Chen, Bingyang, Chen, Tao, Zeng, Xingjie, Zhang, Weishan, Lu, Qinghua, Hou, Zhaoxiang, Zhou, Jiehan, Helal, Sumi

“…Millions of patients suffer from rare diseases around the world. However, the samples of rare diseases are much smaller than those of common diseases…”
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Interwell Stratigraphic Correlation Detection based on knowledge-enhanced few-shot learning by Chen, Bingyang, Zeng, Xingjie, Cao, Shaohua, Zhang, Weishan, Xu, Siyuan, Zhang, Baoyu, Hou, Zhaoxiang

“…Interwell Stratigraphic Correlations Detection (ISCD) guides reservoir modeling and oil development. Many existing AI (artificial intelligence) methods have…”
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Rethinking self-supervised learning for time series forecasting: A temporal perspective by Zhao, Shubao, Zhou, Xinxing, Jin, Ming, Hou, Zhaoxiang, Yang, Chengyi, Li, Zengxiang, Wen, Qingsong, Wang, Yi, Wen, Yanlong, Yuan, Xiaojie

“…Self-supervised learning has garnered significant attention for its ability to learn meaningful representations. Recent advancements have introduced…”
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Knowledge Graph-Based Reinforcement Federated Learning for Chinese Question and Answering by Xu, Liang, Chen, Tao, Hou, Zhaoxiang, Zhang, Weishan, Hon, Chitin, Wang, Xiao, Wang, Di, Chen, Long, Zhu, Wenyin, Tian, Yunlong, Ning, Huansheng, Wang, Fei-Yue

“…Knowledge question and answering (Q&A) is widely used. However, most existing semantic parsing methods in Q&A usually use cascading, which can incur error…”
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SWATM: Contribution-Aware Adaptive Federated Learning Framework Based on Augmented Shapley Values by Yang, Chengyi, Hou, Zhaoxiang, Guo, Sheng, Chen, Hui, Li, Zengxiang

“…The vanilla federated learning (FedAvg) takes a weighted aggregation of uploaded models based on the amount of data from each participant. By addressing…”
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The Prospect of Enhancing Large-Scale Heterogeneous Federated Learning with Transformers by Gao, Yulan, Hou, Zhaoxiang, Yang, Chengyi, Li, Zengxiang, Yu, Han

“…Federated learning (FL) addresses data privacy concerns by enabling collaborative training of AI models across distributed data owners. Wide adoption of FL…”
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The Prospect of Enhancing Large-Scale Heterogeneous Federated Learning with Foundation Models by Gao, Yulan, Hou, Zhaoxiang, Yang, Chengyi, Li, Zengxiang, Yu, Han, Li, Xiaoxiao

“…Federated learning (FL) addresses data privacy concerns by enabling collaborative training of AI models across distributed data owners. Wide adoption of FL…”
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HiMTM: Hierarchical Multi-Scale Masked Time Series Modeling with Self-Distillation for Long-Term Forecasting by Zhao, Shubao, Jin, Ming, Hou, Zhaoxiang, Yang, Chengyi, Li, Zengxiang, Wen, Qingsong, Wang, Yi

“…Time series forecasting is a critical and challenging task in practical application. Recent advancements in pre-trained foundation models for time series…”
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Towards Universal Large-Scale Foundational Model for Natural Gas Demand Forecasting by Zhou, Xinxing, Ye, Jiaqi, Zhao, Shubao, Jin, Ming, Hou, Zhaoxiang, Yang, Chengyi, Li, Zengxiang, Wen, Yanlong, Yuan, Xiaojie

“…In the context of global energy strategy, accurate natural gas demand forecasting is crucial for ensuring efficient resource allocation and operational…”
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FedDRL: A Trustworthy Federated Learning Model Fusion Method Based on Staged Reinforcement Learning by Chen, Leiming, Zhang, Weishan, Dong, Cihao, Qiao, Sibo, Huang, Ziling, Nie, Yuming, Hou, Zhaoxiang, Tan, Chee Wei

“…Traditional federated learning uses the number of samples to calculate the weights of each client model and uses this fixed weight value to fusion the global…”
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Feature-context driven Federated Meta-Learning for Rare Disease Prediction by Chen, Bingyang, Chen, Tao, Zeng, Xingjie, Zhang, Weishan, Lu, Qinghua, Hou, Zhaoxiang, Zhou, Jiehan, Helal, Sumi

“…Millions of patients suffer from rare diseases around the world. However, the samples of rare diseases are much smaller than those of common diseases. In…”
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Federated Learning in Big Model Era: Domain-Specific Multimodal Large Models by Li, Zengxiang, Hou, Zhaoxiang, Liu, Hui, Wang, Ying, Li, Tongzhi, Xie, Longfei, Shi, Chao, Yang, Chengyi, Zhang, Weishan, Liu, Zelei, Xu, Liang

“…Multimodal data, which can comprehensively perceive and recognize the physical world, has become an essential path towards general artificial intelligence…”
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Changes of CD4+CD25+CD127- regulatory T cells in peripheral blood of patients with first-episode depression by Zhang, Yang, Zhang Leijing, Yang, Haibo, Xu, Yang, Hou Zhaoxiang, Zhou, Yueming, Zhao, Yang, Zhao Xiwu

“…ObjectiveTo investigate the changes of CD4+CD25+CD127-/CD4+ ratio in peripheral blood of patients with first-episode depre ssion before and after treatment,…”
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童綜合醫院頭頸部惡性腫瘤臨床病例之分析 by 李佳茹(Chia-Ru Li), 蕭淨玥(Jing-Yueh Hsiao), 溫晨帆(Chen-Fan Wen), 黎瓊柱(Chiung-Chon Li), 陳忠雄(Chunh-Hsiong Chen), 侯昭祥(Chu-Siang Haw), 蔡青劭(Chin-Shaw Tsai)

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