素材网站下载,跨境外贸平台有哪些,网站开发中间商怎么做,台州网站制作建设「DLP-KDD 2021征文」及上届论文全集#xff0c;包含深度学习推荐/广告系统、多目标、模型服务等在DLP-KDD 2021征稿之际#xff0c;为大家准备了DLP-KDD2020的全部文章和资源列表#xff0c;内容涵盖了几乎所有深度学习的业界应用前沿#xff0c;包括深度学习推荐系统应用… 「DLP-KDD 2021征文」及上届论文全集包含深度学习推荐/广告系统、多目标、模型服务等在DLP-KDD 2021征稿之际为大家准备了DLP-KDD2020的全部文章和资源列表内容涵盖了几乎所有深度学习的业界应用前沿包括深度学习推荐系统应用多目标优化BanditLearning to rank模型服务等前沿方向。DLP-KDD作为学术盛会KDD的下设workshop由阿里发起这届workshop由来自阿里巴巴/微软/华为/Roku以及上海交通大学/犹他大学等工业界/学术界资深同行组成主席团旨在促进深度学习在广告、推荐、搜索场景下的应用与业界交流录用文章的工程性实用性很强推荐算法工程师同行们阅读。同时DLP-KDD 2021即将召开欢迎大家积极投稿参与截稿日期2021年5月10日可根据具体情况适当延期所有录用论文将会被ACM-DLhttps://dl.acm.org/doi/proceedings/10.1145/3326937或Springer收录收录详细信息请参照如下征稿文章https://zhuanlan.zhihu.com/p/364358132介绍完DLP-KDD 2021下面为大家介绍上一届DLP-KDD 2020的收录论文及原文链接请点击原文阅读获取全部论文pdf最佳论文COLD-下一代预排序系统 阿里巴巴(Best Paper Award)COLD: Towards the Next Generation of Pre-Ranking System Zhe Wang, Liqin Zhao, Biye Jiang, Guorui Zhou, Xiaoqiang Zhu and Kun Gai业界特点非常强的文章介绍了阿里极高QPS的环境下的深度学习召回/预排序解决方案强烈推荐。最佳论文银奖基于位置Debias场景感知的排序学习方法 美团(Best Paper Runner-Up) Learning-To-Rank with Context-Aware Position DebiasingKeyi Xiao, Xuezhi Cao, Peihao Huang, Sheng Chen, Xiang Zhou, Yunsen XianPosition Debiasing是业界非常令人困扰的问题同样是一篇不可多得的已经在美团场景下应用的工业级文章。最佳论文银奖DCAF-在线服务系统中的动态计算资源分配框架 阿里巴巴(Best Paper Runner-Up)DCAF: A Dynamic Computation Allocation Framework for Online Serving System Biye Jiang, Pengye Zhang, Rihan Chen, Binding Dai, Xinchen Luo, Yin Yang, Guan Wang, Guorui Zhou, Xiaoqiang Zhu and Kun Gai深度学习环境下的计算资源成为非常紧缺的资源需要合理进行分配使用DCAF是阿里巴巴提出的动态计算资源弹性分配框架同样是一篇业界属性非常强的实用文章。其他录用文章Selling Products by Machine: a User-Sensitive Adversarial Training method for Short Title Generation in Mobile E-CommerceManyi Wang, Tao Zhang, Qijin Chen, Chengfu Huo and Weijun RenxDeepInt: a hybrid architecture for modeling the vector-wise and bit-wise feature interactions Yachen Yan and Liubo LiFLEN: Leveraging Field for Scalable CTR Prediction Wenqiang Chen, Lizhang Zhan, Yuanlong Ci, Minghua Yang, Chen Lin and Dugang LiuRanking with Deep Multi-Objective Learning Xuezhi Cao, Sheng Zhu, Biao Tang, Rui Xie, Fuzheng Zhang and Zhongyuan WangCategorization of Social Actors in Social Network Analysis (SNA) using Representation Learning via Knowledge-Graph Embeddings and Convolution Operations (RLVECO) Bonaventure Molokwu, Shaon Bhatta Shuvo and Ziad KobtiAutoencoder Anomaly Detection on Large CAN Bus Data Elena Novikova, Vu Le, Matvey Yutin, Michael Weber and Cory AndersonPersonalized Re-ranking for Improving Diversity in Live Recommender Systems Yichao Wang, Xiangyu Zhang, Zhirong Liu, Zhenhua Dong, Xinhua Feng, Ruiming Tang and Xiuqiang HeDistilled Bandit for Real-time Online Optimization Ziying Liu, Yu Sun, Jianjie Ma, Haiyan Luo, Yujing Wu and Elizabeth LattanzioReview Regularized Neural Collaborative Filtering Zhimeng Pan, Wenzheng Tao and Qingyao AiTraining Deep Learning Recommendation Model with Quantized Collective Communications Jie Yang, Jongsoo Park, Srinivas Sridharan and Ping Tak Peter TangCorrect Normalization Matters: Understanding the Effect of Normalization On Deep Neural Network Models For Click-Through Rate Prediction Zhiqiang Wang, Qingyun She, Pengtao Zhang and Junlin ZhangPinText 2: Attentive Bag of Annotations Embedding Jinfeng Zhuang, Jennifer Zhao, Anant Subramanian, Yun Lin, Balaji Krishnapuram and Roelof ZwolAnomaly detection for sparse data A framework based on PU-Learning and GAN’sAndrew Shields and Ted ScullyAutomated Model Selection for Time-Series Anomaly Detection Yuanxiang Ying, Juanyong Duan, Chunlei Wang, Yujing Wang, Congrui Huang and Bixiong XuPareCO: Pareto-aware Channel Optimization for Slimmable Neural Networks Ting-Wu Chin, Ari Morcos and Diana MarculescuDLP-KDD 2021研讨会相关安排Workshop官方网站https://dlp-kdd.github.io论文提交系统https://easychair.org/account/signin?l3xYwWMZmH6WsGJLCgb8CIT#论文要求短文(2-4页) or 长文(不超过9页)均可征文截稿时间2021-05-10征文投稿录用情况通知2021-06-10研讨会召开时间与地点第三届DLP-KDD workshop将于2021-08-10到14日以虚拟形式的会议召开并在北京设立线下分会场具体地点待定所有录用文章将会被ACM DLACM Digital Library或Springer收录凭作者意愿关于本次Workshop的一切问题也可知乎私信咨询主席团成员 朱小强周国睿王喆Weinan Zhang 等通过上一届论文的介绍大家可以看到DLP-KDD非常欢迎业界工程师的文章投稿我们欢迎业界一线的模型及相关基础设施、架构的应用、改进经验。包括但不限于模型改进BertTransformer多目标学习LTR深度学习模型结构Attention等、模型服务、线上推荐流程等方向欢迎大家投稿并参加线下及线上的业界讨论交流。请点击原文阅读链接获取全部论文下载链接 。复制链接内容直接发送到微信对话框链接即可直接打开