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4篇 您的检索式:作者名="Junchi Yan"
    题名 作者 年代 出处 被引量
1Visual saliency detection via sparsity pursuit显示文摘YAN Junchi ZHU Mengyuan LIU Yuneai 2010IEEE Signal Processing Letters2010,17,8:1
2Visual saliency detection via sparsity pursuit 显示文摘Yan Junchi Zhu Mengyuan Liu Huanxi 2010IEEE Signal Processing Letters2010,17,8:1
34350<ce:hsp sp='0.25'/>W quasi-continuous-wave operation of a diode face-pumped ceramic Nd: YAG slab laser显示文摘Junchi Chen Jiang Li Jialin Xu Wenbin Liu Yong Bo Xiqi Feng Yiting Xu Dongliang Jiang Zhongzheng Chen Yubai Pan Yading Guo Biao Yan Chang Guo Lei Yuan Hongtao Yuan Yanyong Lin Yunsheng Xiao Qinjun Peng Wenqiang Lei Dafu Cui Zuyan Xu 2014Optics and Laser Technology2014,,:1
4Machine Learning Methods in Solving the Boolean Satisfiability Problem显示文摘This paper reviews the recent literature on solving the Boolean satisfiability problem(SAT),an archetypal N P-complete problem,with the aid of machine learning(ML)techniques.Over the last decade,the machine learning society advances rapidly and surpasses human performance on several tasks.This trend also inspires a number of works that apply machine learning methods for SAT solving.In this survey,we examine the evolving ML SAT solvers from naive classifiers with handcrafted features to emerging end-to-end SAT solvers,as well as recent progress on combinations of existing conflict-driven clause learning(CDCL)and local search solvers with machine learning methods.Overall,solving SAT with machine learning is a promising yet challenging research topic.We conclude the limitations of current works and suggest possible future directions.The collected paper list is available at http://gffzz188fe103f8f1460asqocnv6cfx5pn6095.ffgz.tsg.suse.edu.cn/ThinklabSJTU/awesome-ml4co.Keywords:Machine learning(ML),Boolean satisfiability(SAT),deep learning,graph neural networks(GNNs),combinatorial optimization.Wenxuan Guo Hui-Ling Zhen Xijun Li Wanqian Luo Mingxuan Yuan Yaohui Jin Junchi Yan 2023Machine Intelligence Research2023,20,5:0
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