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文献阅读(57)ICML Workshop2020-Deep Graph Contrastive Representation Learning
本文是对《Deep Graph Contrastive Representation Learning》一文的浅显翻译与理解,如有侵权即刻删除。 更多相关文章,请移步: 文献阅读总结:网络表示学习 文章目录 Title总结1 问题定义2 对比学习框架3 视图生成3.1 边舍弃3.2 节点特征掩码 Title 《Deep Graph ContrastiTwo-way Partial AUC优化(ICML-2021,oral)
今天给大家的分享的是我们在ICML-2021上发表的一篇AUC优化的文章**《When All We Need is a Piece of the Pie: A Generic Framework for Optimizing Two-way Partial AUC》**被ICML 2021以长文形式接收。 ICML全称是International Conference on Machine Learning,是机器学[RL 13] QMIX (ICML, 2018, Oxford)
论文: QMIX: Monotonic Value Function Factorisation for Deep Multi-Agent Reinforcement Learning 背景 同VDN 4. QMIX 假设 Qtot 与 Qi 有如(4)式的关系. (4)式可以通过(5)式实现. (5)式可以通过如下Fig2的QMIX网络架构实现 agent networks: 进行local决策 即DRQN,ICML联邦学习论文解读 SCAFFOLD: Stochastic Controlled Averaging for Federated Learning
论文解读:SCAFFOLD: Stochastic Controlled Averaging for Federated Learning 作者:Sai Praneeth Karimireddy, Satyen Kale, Mehryar Mohri,Sashank J. Reddi, Sebastian U. Stich, Ananda Theertha Suresh 论文地址:https://arxiv.org/abs/1910.06378 一、背景介绍 联邦学习2020 ICML 全部论文
All Papers 38 - ShapeCaptioner: Generative Caption Network for 3D Shapes by Learning a Mapping from Parts Detected in Multiple Views to Sentences "Zhizhong Han (University of Maryland, College Park); Chao Chen (Tsinghua University); Yu-Shen Liu (Tsin《元学习:从Few-Shot学习到快速强化学习(ICML 2019 Tutorial) by Chelsea Finn, Sergey Levine》
元学习:从Few-Shot学习到快速强化学习(ICML 2019 Tutorial) by Chelsea Finn, Sergey Levine https://www.bilibili.com/video/BV1o4411A7YE人工智能顶级会议列表
【摘抄,可能已过时】 机器学习顶级会议:NIPS, ICML, UAI, AISTATS; (期刊:JMLR, ML, Trends in ML, IEEE T-NN) 计算机视觉和图像识别:ICCV, CVPR, ECCV; (期刊:IEEE T-PAMI, IJCV, IEEE T-IP) 人工智能:IJCAI, AAAI; (期刊AI) 另外相关的还有SIGRAPH, KDD, ACL, SIGIR, WWW等。 特