{"id":10,"date":"2024-02-04T14:45:04","date_gmt":"2024-02-04T06:45:04","guid":{"rendered":"http:\/\/daqings.net\/?page_id=10"},"modified":"2025-12-08T11:12:41","modified_gmt":"2025-12-08T03:12:41","slug":"qing-da-%e7%ac%aa%e5%ba%86s-homepage","status":"publish","type":"page","link":"http:\/\/daqings.net\/","title":{"rendered":"Qing Da (\u7b2a\u5e86)&#8217;s Homepage"},"content":{"rendered":"<p><a href=\"daqingacm@sina.com\">E-mail<\/a> \/ <a href=\"https:\/\/scholar.google.com\/citations?user=sRKGtmgAAAAJ&amp;hl=en\">Google scholar<\/a> \/ <a href=\"https:\/\/dblp.org\/pid\/138\/2474.html\">DBLP<\/a> \/ <a href=\"http:\/\/daqings.net\/?page_id=83\">\u4e2d\u6587\u7248<\/a><\/p>\n<p data-path-to-node=\"5\">Formerly a Senior Algorithm Expert at Alibaba (Alias: Da Qing). Both his Bachelor&#8217;s and Master&#8217;s degrees were obtained from the Department of Computer Science and Technology at Nanjing University, supervised by Professor Zhi-Hua Zhou, focusing on machine learning research. In early 2015, he withdrew from his Ph.D. program during the second year to join Alibaba&#8217;s Search and Recommendation Division, working on search and recommendation algorithms.<\/p>\n<p data-path-to-node=\"6\">During his tenure at Alibaba, in addition to his core responsibilities, he was involved in training new algorithm talents. He was a co-author of the 2019 group newcomer course &#8220;Introduction to Search, Recommendation, and Advertising Algorithm Systems&#8221; and served as the main lecturer for the Hangzhou session. He also served as the head teacher for the Search and Recommendation Division&#8217;s algorithm newcomer class in 2020. Externally, he has served as a reviewer for top-tier journals and conferences such as TNNLS, AAAI, IJCAI, and ICML.<\/p>\n<p data-path-to-node=\"7\">He joined ByteDance in October 2022, focusing on e-commerce algorithms.<\/p>\n<h2><b>Education<\/b><\/h2>\n<p class=\"my-2 [&amp;+p]:mt-4 [&amp;_strong:has(+br)]:inline-block [&amp;_strong:has(+br)]:pb-2\"><strong>Bachelor&#8217;s Degree<\/strong>: Nanjing University, Department of Computer Science and Technology, September 2006 \u2013 June 2010<\/p>\n<ul class=\"marker:text-quiet list-disc\">\n<li class=\"py-0 my-0 prose-p:pt-0 prose-p:mb-2 prose-p:my-0 [&amp;&gt;p]:pt-0 [&amp;&gt;p]:mb-2 [&amp;&gt;p]:my-0\">\n<p class=\"my-2 [&amp;+p]:mt-4 [&amp;_strong:has(+br)]:inline-block [&amp;_strong:has(+br)]:pb-2\">First Place (National First Prize) in the National Undergraduate Mathematical Modeling Competition, first author, 2008<\/p>\n<\/li>\n<li class=\"py-0 my-0 prose-p:pt-0 prose-p:mb-2 prose-p:my-0 [&amp;&gt;p]:pt-0 [&amp;&gt;p]:mb-2 [&amp;&gt;p]:my-0\">\n<p class=\"my-2 [&amp;+p]:mt-4 [&amp;_strong:has(+br)]:inline-block [&amp;_strong:has(+br)]:pb-2\">Ministry of Education &#8211; Sun Microsystems University Student Innovation Experimental Plan Outstanding Project, first author, 2009<\/p>\n<\/li>\n<li class=\"py-0 my-0 prose-p:pt-0 prose-p:mb-2 prose-p:my-0 [&amp;&gt;p]:pt-0 [&amp;&gt;p]:mb-2 [&amp;&gt;p]:my-0\">\n<p class=\"my-2 [&amp;+p]:mt-4 [&amp;_strong:has(+br)]:inline-block [&amp;_strong:has(+br)]:pb-2\">Nanjing University Undergraduate Excellent Thesis (Design) First Prize, 2010<\/p>\n<\/li>\n<li class=\"py-0 my-0 prose-p:pt-0 prose-p:mb-2 prose-p:my-0 [&amp;&gt;p]:pt-0 [&amp;&gt;p]:mb-2 [&amp;&gt;p]:my-0\">\n<p class=\"my-2 [&amp;+p]:mt-4 [&amp;_strong:has(+br)]:inline-block [&amp;_strong:has(+br)]:pb-2\">Recommended to continue graduate studies in the same department (Rank 1st)<\/p>\n<\/li>\n<\/ul>\n<p class=\"my-2 [&amp;+p]:mt-4 [&amp;_strong:has(+br)]:inline-block [&amp;_strong:has(+br)]:pb-2\"><strong>Master&#8217;s Degree<\/strong>: Nanjing University, Department of Computer Science and Technology, Machine Learning and Data Mining Laboratory (LAMDA), September 2010 \u2013 June 2013<\/p>\n<ul class=\"marker:text-quiet list-disc\">\n<li class=\"py-0 my-0 prose-p:pt-0 prose-p:mb-2 prose-p:my-0 [&amp;&gt;p]:pt-0 [&amp;&gt;p]:mb-2 [&amp;&gt;p]:my-0\">\n<p class=\"my-2 [&amp;+p]:mt-4 [&amp;_strong:has(+br)]:inline-block [&amp;_strong:has(+br)]:pb-2\">PAKDD Data Mining Competition Public Division Champion, fifth author, 2012<\/p>\n<\/li>\n<li class=\"py-0 my-0 prose-p:pt-0 prose-p:mb-2 prose-p:my-0 [&amp;&gt;p]:pt-0 [&amp;&gt;p]:mb-2 [&amp;&gt;p]:my-0\">\n<p class=\"my-2 [&amp;+p]:mt-4 [&amp;_strong:has(+br)]:inline-block [&amp;_strong:has(+br)]:pb-2\">First &#8220;China Cloud \u00b7 Mobile Internet Innovation Award,&#8221; One First Prize, One Second Prize, Two Third Prizes, first author, 2013.<\/p>\n<\/li>\n<li class=\"py-0 my-0 prose-p:pt-0 prose-p:mb-2 prose-p:my-0 [&amp;&gt;p]:pt-0 [&amp;&gt;p]:mb-2 [&amp;&gt;p]:my-0\">\n<p class=\"my-2 [&amp;+p]:mt-4 [&amp;_strong:has(+br)]:inline-block [&amp;_strong:has(+br)]:pb-2\">Master&#8217;s Thesis: &#8220;Research on Reinforcement Learning Methods Based on Direct Policy Search&#8221;<\/p>\n<\/li>\n<\/ul>\n<p class=\"my-2 [&amp;+p]:mt-4 [&amp;_strong:has(+br)]:inline-block [&amp;_strong:has(+br)]:pb-2\"><strong>PhD (Incomplete)<\/strong>: Nanjing University, Department of Computer Science and Technology, Machine Learning and Data Mining Laboratory (LAMDA), September 2013 \u2013 January 2015, Discontinued<\/p>\n<ul class=\"marker:text-quiet list-disc\">\n<li class=\"py-0 my-0 prose-p:pt-0 prose-p:mb-2 prose-p:my-0 [&amp;&gt;p]:pt-0 [&amp;&gt;p]:mb-2 [&amp;&gt;p]:my-0\">\n<p class=\"my-2 [&amp;+p]:mt-4 [&amp;_strong:has(+br)]:inline-block [&amp;_strong:has(+br)]:pb-2\">During the first year of PhD, published one CCF A-class paper [2006-2] and one CCF B-class paper [2006-3] as first author. Mid-program evaluation ranked excellent (Rank 1st).<\/p>\n<\/li>\n<li class=\"py-0 my-0 prose-p:pt-0 prose-p:mb-2 prose-p:my-0 [&amp;&gt;p]:pt-0 [&amp;&gt;p]:mb-2 [&amp;&gt;p]:my-0\">\n<p class=\"my-2 [&amp;+p]:mt-4 [&amp;_strong:has(+br)]:inline-block [&amp;_strong:has(+br)]:pb-2\">Withdrew from studies at the beginning of the second year for personal reasons to enter industry.<\/p>\n<\/li>\n<\/ul>\n<h2><b>Professional Experience<\/b><\/h2>\n<p class=\"my-2 [&amp;+p]:mt-4 [&amp;_strong:has(+br)]:inline-block [&amp;_strong:has(+br)]:pb-2\"><strong>January 2015 \u2013 June 2016: Senior Algorithm Engineer<\/strong>, Search Business Unit, Alibaba<\/p>\n<ul class=\"marker:text-quiet list-disc\">\n<li class=\"py-0 my-0 prose-p:pt-0 prose-p:mb-2 prose-p:my-0 [&amp;&gt;p]:pt-0 [&amp;&gt;p]:mb-2 [&amp;&gt;p]:my-0\">\n<p class=\"my-2 [&amp;+p]:mt-4 [&amp;_strong:has(+br)]:inline-block [&amp;_strong:has(+br)]:pb-2\">Engaged in Taobao search algorithm development work<\/p>\n<\/li>\n<li class=\"py-0 my-0 prose-p:pt-0 prose-p:mb-2 prose-p:my-0 [&amp;&gt;p]:pt-0 [&amp;&gt;p]:mb-2 [&amp;&gt;p]:my-0\">\n<p class=\"my-2 [&amp;+p]:mt-4 [&amp;_strong:has(+br)]:inline-block [&amp;_strong:has(+br)]:pb-2\">Through collaboration with the engineering team, successfully deployed the first version of a large-scale online learning model based on parameter server, promoting the widespread application of online learning in Taobao search. The related work &#8220;Real-time Personalization for Taobao Search Based on Online Matrix Factorization&#8221; won the 2015 Group Top Ten Algorithm Award<\/p>\n<\/li>\n<li class=\"py-0 my-0 prose-p:pt-0 prose-p:mb-2 prose-p:my-0 [&amp;&gt;p]:pt-0 [&amp;&gt;p]:mb-2 [&amp;&gt;p]:my-0\">\n<p class=\"my-2 [&amp;+p]:mt-4 [&amp;_strong:has(+br)]:inline-block [&amp;_strong:has(+br)]:pb-2\">First introduced the technology of optimal allocation combined with PID online adjustment to Singles&#8217; Day red envelope distribution. This technology has become the foundational general solution for group-wide rights distribution and traffic control, and resulted in the patent &#8220;A Method for Distributing Red Envelopes via Keywords to Sell Traffic&#8221;<\/p>\n<\/li>\n<li class=\"py-0 my-0 prose-p:pt-0 prose-p:mb-2 prose-p:my-0 [&amp;&gt;p]:pt-0 [&amp;&gt;p]:mb-2 [&amp;&gt;p]:my-0\">\n<p class=\"my-2 [&amp;+p]:mt-4 [&amp;_strong:has(+br)]:inline-block [&amp;_strong:has(+br)]:pb-2\">Recipient of the 2015 Search Business Unit New Employee Award, Double Eleven Crazy Search Person Award, and Technology Excellence Award team member<\/p>\n<\/li>\n<li class=\"py-0 my-0 prose-p:pt-0 prose-p:mb-2 prose-p:my-0 [&amp;&gt;p]:pt-0 [&amp;&gt;p]:mb-2 [&amp;&gt;p]:my-0\">\n<p class=\"my-2 [&amp;+p]:mt-4 [&amp;_strong:has(+br)]:inline-block [&amp;_strong:has(+br)]:pb-2\">Multiple internal group algorithm competition awards: Runner-up in Sina Weibo Interaction Prediction Competition; Runner-up in Resume Intelligent Scoring Competition; Cainiao Demand Forecasting &amp; Warehouse Planning Winning Award (rank 4)<\/p>\n<\/li>\n<\/ul>\n<p class=\"my-2 [&amp;+p]:mt-4 [&amp;_strong:has(+br)]:inline-block [&amp;_strong:has(+br)]:pb-2\"><strong>July 2016 \u2013 December 2017: Algorithm Expert<\/strong>, Search Business Unit, Alibaba<\/p>\n<ul class=\"marker:text-quiet list-disc\">\n<li class=\"py-0 my-0 prose-p:pt-0 prose-p:mb-2 prose-p:my-0 [&amp;&gt;p]:pt-0 [&amp;&gt;p]:mb-2 [&amp;&gt;p]:my-0\">\n<p class=\"my-2 [&amp;+p]:mt-4 [&amp;_strong:has(+br)]:inline-block [&amp;_strong:has(+br)]:pb-2\">First introduced reinforcement learning into e-commerce search ranking, with online application during the 2016 Double Eleven shopping festival, covered by multiple media outlets.\u00a0<span class=\"text-box-trim-both\">Machine Heart Report<\/span><\/p>\n<\/li>\n<li class=\"py-0 my-0 prose-p:pt-0 prose-p:mb-2 prose-p:my-0 [&amp;&gt;p]:pt-0 [&amp;&gt;p]:mb-2 [&amp;&gt;p]:my-0\">\n<p class=\"my-2 [&amp;+p]:mt-4 [&amp;_strong:has(+br)]:inline-block [&amp;_strong:has(+br)]:pb-2\">Designed and implemented the AI4B-RL reinforcement learning framework for internal search, applied reinforcement learning across multiple business lines, including search ranking [2018-2], product display learning [2018-3], engine performance optimization [2021\/2022-6], seller stratification control, traffic control, virtual Taobao [2019-3], and other projects. Related work has been published in KDD, AAAI, and ECML.<\/p>\n<\/li>\n<li class=\"py-0 my-0 prose-p:pt-0 prose-p:mb-2 prose-p:my-0 [&amp;&gt;p]:pt-0 [&amp;&gt;p]:mb-2 [&amp;&gt;p]:my-0\">\n<p class=\"my-2 [&amp;+p]:mt-4 [&amp;_strong:has(+br)]:inline-block [&amp;_strong:has(+br)]:pb-2\">Organized all related algorithm teams across the group and published an e-book &#8220;<a href=\"https:\/\/www.jiqizhixin.com\/articles\/2018-02-06-3\">Technical Evolution and Business Innovation of Reinforcement Learning at Alibaba<\/a>,&#8221; covering broad domains including search, recommendation, advertising, logistics, and intelligent customer service. The book was subsequently published in physical form by Electronic Industry Press.<\/p>\n<\/li>\n<\/ul>\n<p class=\"my-2 [&amp;+p]:mt-4 [&amp;_strong:has(+br)]:inline-block [&amp;_strong:has(+br)]:pb-2\"><strong>January 2018 \u2013 July 2020: Senior Algorithm Expert<\/strong>, AI International Business Unit, Alibaba<\/p>\n<ul class=\"marker:text-quiet list-disc\">\n<li class=\"py-0 my-0 prose-p:pt-0 prose-p:mb-2 prose-p:my-0 [&amp;&gt;p]:pt-0 [&amp;&gt;p]:mb-2 [&amp;&gt;p]:my-0\">\n<p class=\"my-2 [&amp;+p]:mt-4 [&amp;_strong:has(+br)]:inline-block [&amp;_strong:has(+br)]:pb-2\">Led a team to participate in the OpenAI-hosted reinforcement learning algorithm competition, winning the global championship, as first author.\u00a0<span class=\"text-box-trim-both\"><a href=\"https:\/\/openai.com\/research\/retro-contest-results\">OpenAI Official News<\/a> | <\/span><a href=\"https:\/\/mp.weixin.qq.com\/s\/3u9YTLGBXYDwFcpZbfrv6Q\"><span class=\"text-box-trim-both\">Alibaba Technical Report<\/span><\/a><\/p>\n<\/li>\n<li class=\"py-0 my-0 prose-p:pt-0 prose-p:mb-2 prose-p:my-0 [&amp;&gt;p]:pt-0 [&amp;&gt;p]:mb-2 [&amp;&gt;p]:my-0\">\n<p class=\"my-2 [&amp;+p]:mt-4 [&amp;_strong:has(+br)]:inline-block [&amp;_strong:has(+br)]:pb-2\">Starting August 2018, assumed the role of AliExpress Search Algorithm Lead, building a team and driving technology upgrades tailored to international business characteristics. The seed team of 2-3 people has grown into a 20+ algorithm team, covering four sub-directions: search relevance, search efficiency, search discovery products, and traffic control. Over two consecutive fiscal years, search conversion rates improved by 30% and 20% respectively over the baseline that had been optimized for 8 years, with significant improvements in search relevance, search discovery products, and related business metrics.<\/p>\n<\/li>\n<li class=\"py-0 my-0 prose-p:pt-0 prose-p:mb-2 prose-p:my-0 [&amp;&gt;p]:pt-0 [&amp;&gt;p]:mb-2 [&amp;&gt;p]:my-0\">\n<p class=\"my-2 [&amp;+p]:mt-4 [&amp;_strong:has(+br)]:inline-block [&amp;_strong:has(+br)]:pb-2\">Addressing multilingual challenges in international business, began researching cross-lingual vector models around the same time Facebook proposed XLM, currently covering English, Russian, Spanish, French, and Portuguese, fully deployed for semantic vector recall in search [2021\/2022-3]. To address difficulties international sellers face in title writing, established relationships between images and keywords to assist in title completion. This work was organized and published at PAKDD [2021\/2022-2].<\/p>\n<\/li>\n<li class=\"py-0 my-0 prose-p:pt-0 prose-p:mb-2 prose-p:my-0 [&amp;&gt;p]:pt-0 [&amp;&gt;p]:mb-2 [&amp;&gt;p]:my-0\">\n<p class=\"my-2 [&amp;+p]:mt-4 [&amp;_strong:has(+br)]:inline-block [&amp;_strong:has(+br)]:pb-2\">Given that single models struggle to capture behavioral differences across global users, upgraded the classical MOE structure to a hierarchical MOE structure, using scenario sub-networks and scenario gradient isolation to ensure final fusion effectiveness. This work has been fully deployed online and was accepted at CIKM&#8217;20 [2020-2].<\/p>\n<\/li>\n<li class=\"py-0 my-0 prose-p:pt-0 prose-p:mb-2 prose-p:my-0 [&amp;&gt;p]:pt-0 [&amp;&gt;p]:mb-2 [&amp;&gt;p]:my-0\">\n<p class=\"my-2 [&amp;+p]:mt-4 [&amp;_strong:has(+br)]:inline-block [&amp;_strong:has(+br)]:pb-2\">For the re-ranking scenario, to capture user behavior preferences regarding overall product arrangement, proposed a learning-to-rank framework based on an evaluator-generator architecture that can directly generate product arrangements to optimize full-page user behavior. This work has been deployed online and was published in TKDE [2023-1], with related <a href=\"https:\/\/www.jiqizhixin.com\/articles\/2020-04-03-3?from=synced&amp;keyword=%E9%AA%8C%E8%AF%81%E9%9B%86%E8%AF%84%E4%BC%B0%E5%8F%AF%E8%83%BD%E6%98%AF%E9%94%99%E7%9A%84\">media coverage<\/a><\/p>\n<\/li>\n<\/ul>\n<p class=\"my-2 [&amp;+p]:mt-4 [&amp;_strong:has(+br)]:inline-block [&amp;_strong:has(+br)]:pb-2\"><strong>August 2020 \u2013 September 2021: Senior Algorithm Expert<\/strong>, AE Technology Department, Alibaba<\/p>\n<ul class=\"marker:text-quiet list-disc\">\n<li class=\"py-0 my-0 prose-p:pt-0 prose-p:mb-2 prose-p:my-0 [&amp;&gt;p]:pt-0 [&amp;&gt;p]:mb-2 [&amp;&gt;p]:my-0\">\n<p class=\"my-2 [&amp;+p]:mt-4 [&amp;_strong:has(+br)]:inline-block [&amp;_strong:has(+br)]:pb-2\">Designed and productized the AliExpress traffic control system for efficient integration of commercial and efficiency strategies. Related work includes online matching [2021\/2022-7] published at AAAI 2021, with remaining components currently under review [2021\/2022-10].<\/p>\n<\/li>\n<li class=\"py-0 my-0 prose-p:pt-0 prose-p:mb-2 prose-p:my-0 [&amp;&gt;p]:pt-0 [&amp;&gt;p]:mb-2 [&amp;&gt;p]:my-0\">\n<p class=\"my-2 [&amp;+p]:mt-4 [&amp;_strong:has(+br)]:inline-block [&amp;_strong:has(+br)]:pb-2\">Currently serves as AliExpress Search Algorithm Lead and additionally holds the role of AliExpress Algorithm Architect, responsible for cross-functional capability building for AliExpress&#8217;s multiple business algorithm lines including search, recommendation, advertising, and user growth.<\/p>\n<\/li>\n<\/ul>\n<p class=\"my-2 [&amp;+p]:mt-4 [&amp;_strong:has(+br)]:inline-block [&amp;_strong:has(+br)]:pb-2\"><strong>October 2022 \u2013 May 2024: Head of Content E-Commerce Recommendation Algorithm<\/strong>, ByteDance (Douyin)<\/p>\n<ul class=\"marker:text-quiet list-disc\">\n<li class=\"py-0 my-0 prose-p:pt-0 prose-p:mb-2 prose-p:my-0 [&amp;&gt;p]:pt-0 [&amp;&gt;p]:mb-2 [&amp;&gt;p]:my-0\">\n<p class=\"my-2 [&amp;+p]:mt-4 [&amp;_strong:has(+br)]:inline-block [&amp;_strong:has(+br)]:pb-2\">Led a team on content distribution e-commerce content types on Douyin, including but not limited to shopping cart videos, store anchor videos, e-commerce video avatars, e-commerce live streams, and non-linked e-commerce intent videos. Responsible for improving matching efficiency between users and e-commerce content while meeting user content interaction constraints, optimizing pre-purchase and post-purchase user experience, fostering effective interaction with e-commerce primary scenarios (such as shopping malls and store windows), and enhancing overall e-commerce penetration and transaction scale.<\/p>\n<\/li>\n<li class=\"py-0 my-0 prose-p:pt-0 prose-p:mb-2 prose-p:my-0 [&amp;&gt;p]:pt-0 [&amp;&gt;p]:mb-2 [&amp;&gt;p]:my-0\">\n<p class=\"my-2 [&amp;+p]:mt-4 [&amp;_strong:has(+br)]:inline-block [&amp;_strong:has(+br)]:pb-2\">Key projects include: e-commerce traffic framework establishment, e-commerce interest capture, balance between content experience and e-commerce efficiency, consumer growth technology, and e-commerce traffic control systems.<\/p>\n<\/li>\n<\/ul>\n<p class=\"my-2 [&amp;+p]:mt-4 [&amp;_strong:has(+br)]:inline-block [&amp;_strong:has(+br)]:pb-2\"><strong>June 2024 \u2013 Present: Head of TikTok E-Commerce Search Algorithm<\/strong>, ByteDance<\/p>\n<ul class=\"marker:text-quiet list-disc\">\n<li class=\"py-0 my-0 prose-p:pt-0 prose-p:mb-2 prose-p:my-0 [&amp;&gt;p]:pt-0 [&amp;&gt;p]:mb-2 [&amp;&gt;p]:my-0\">\n<p class=\"my-2 [&amp;+p]:mt-4 [&amp;_strong:has(+br)]:inline-block [&amp;_strong:has(+br)]:pb-2\">Leading a team on TikTok e-commerce search algorithm optimization, covering all consumer-facing e-commerce search scenarios including TikTok general search e-commerce, shopping mall search, and image search.<\/p>\n<\/li>\n<li class=\"py-0 my-0 prose-p:pt-0 prose-p:mb-2 prose-p:my-0 [&amp;&gt;p]:pt-0 [&amp;&gt;p]:mb-2 [&amp;&gt;p]:my-0\">\n<p class=\"my-2 [&amp;+p]:mt-4 [&amp;_strong:has(+br)]:inline-block [&amp;_strong:has(+br)]:pb-2\">Key projects include: Query understanding and relevance optimization, full-link efficiency optimization for search including retrieval\/coarse ranking\/fine ranking\/mixed ranking, and e-commerce experience and ecosystem cold-start optimization.<\/p>\n<\/li>\n<\/ul>\n<h2><b>Publications<\/b><\/h2>\n<p class=\"my-2 [&amp;+p]:mt-4 [&amp;_strong:has(+br)]:inline-block [&amp;_strong:has(+br)]:pb-2\"><strong>BOOK<\/strong><\/p>\n<p class=\"my-2 [&amp;+p]:mt-4 [&amp;_strong:has(+br)]:inline-block [&amp;_strong:has(+br)]:pb-2\"><strong>Da Qing, Zeng Anxiang (Editors). Reinforcement Learning in Practice: Technical Evolution and Business Innovation of Reinforcement Learning at Alibaba. Electronic Industry Press, 2018.<\/strong><\/p>\n<p class=\"my-2 [&amp;+p]:mt-4 [&amp;_strong:has(+br)]:inline-block [&amp;_strong:has(+br)]:pb-2\"><strong>OPEN SOURCE RECOMMENDATION SYSTEM ENVIRONMENT<\/strong><\/p>\n<p class=\"my-2 [&amp;+p]:mt-4 [&amp;_strong:has(+br)]:inline-block [&amp;_strong:has(+br)]:pb-2\"><strong>VirtualTaobao<\/strong>\u00a0[AAAI&#8217;19],\u00a0<a class=\"reset interactable cursor-pointer decoration-1 underline-offset-1 text-super hover:underline font-semibold\" href=\"https:\/\/github.com\/\" target=\"_blank\" rel=\"nofollow noopener\"><span class=\"text-box-trim-both\">Github<\/span><\/a>: This project provides a VirtualTaobao simulator trained on actual Taobao data, addressing the problem of evaluating learning strategies in traditional recommendation system models using biased offline data. At Taobao, when a customer inputs a search query, the recommendation system returns a series of products based on the query and customer information. The system aims to return a product list with high click probability. Through the VirtualTaobao simulator, users can access a &#8220;real-time&#8221; environment similar to the actual Taobao environment. Each session generates a virtual customer who initiates a search query, and the recommendation system must return a series of products. The virtual customer decides whether to click on products in the returned list, similar to real customers. The training procedure of VirtualTaobao is described in the original paper:<\/p>\n<ul>\n<li>Jing-Cheng Shi, Yang Yu, <b>Qing Da<\/b>, Shi-Yong Chen, An-Xiang Zeng. Virtual-Taobao: Virtualizing real-world online retail environment for reinforcement learning. In: <b style=\"background-color: var(--global--color-background); color: var(--global--color-primary); font-family: var(--global--font-secondary); font-size: var(--global--font-size-base);\">Proceedings of the 33rd AAAI Conference on Artificial <\/b><b style=\"background-color: var(--global--color-background); color: var(--global--color-primary); font-family: var(--global--font-secondary); font-size: var(--global--font-size-base);\">Intelligence (AAAI\u201919)<\/b><span style=\"background-color: var(--global--color-background); color: var(--global--color-primary); font-family: var(--global--font-secondary); font-size: var(--global--font-size-base);\">, Honolulu, HI, 2019. PDF<\/span><\/li>\n<\/ul>\n<div data-page-id=\"DTbRdkCnEoS2XIxUfWlcYI7MnZf\" data-docx-has-block-data=\"false\">\n<h3 class=\"ace-line ace-line old-record-id-W3zad2tMOoJezdxrha9cxR5enHc\">2023<\/h3>\n<div class=\"ace-line ace-line old-record-id-GoFjd6s2ko428axUOgRcd8m2n1e\">[1] Guangda Huzhang, Zhen-Jia Pang, Yongqing Gao, Yawen Liu, Weijie Shen, Wen-Ji Zhou, Qianying Lin, <strong>Qing Da<\/strong>, Anxiang Zeng, Han Yu, Yang Yu, Zhi-Hua Zhou: AliExpress Learning-to-Rank: Maximizing Online Model Performance Without Going Online. <strong>IEEE Trans. Knowl. Data Eng<\/strong>. 35(2): 1214-1226 (2023)<\/div>\n<p>&nbsp;<\/p>\n<h3 class=\"ace-line ace-line old-record-id-OqlqdCfq4oG7NIxaYB8cn1WGnFf\">2021\/2022<\/h3>\n<div class=\"ace-line ace-line old-record-id-P47LdW9ehojDm8x2qEicY2iznpg\">[1] Qianying Lin, Wen-Ji Zhou, Yanshi Wang, <strong>Qing Da<\/strong>, Qing-Guo Chen, Bing Wang: Sparse Attentive Memory Network for Click-through Rate Prediction with Long Sequences. <strong>CIKM 2022<\/strong>: 3312-3321<\/div>\n<div class=\"ace-line ace-line old-record-id-SSPNdE0DDoaFK2xx6xRclhDLnSe\">[2] Wenya Zhu, Yinghua Zhang, Yu Zhang, Yu-Hang Zhou, Yinfu Feng, Yuxiang Wu, <strong>Qing Da<\/strong>, Anxiang Zeng: DHA: Product Title Generation with Discriminative Hierarchical Attention for E-commerce. <strong>PAKDD<\/strong> (3) 2022: 275-287<\/div>\n<div class=\"ace-line ace-line old-record-id-DwF3dyPEiof5QLxKYczcTDnXnEh\">[3] Wenya Zhu, Xiaoyu Lv, Baosong Yang, Yinghua Zhang, Xu Yong, Linlong Xu, Yinfu Feng, Haibo Zhang, <strong>Qing Da<\/strong>, Anxiang Zeng, Ronghua Chen: Cross-Lingual Product Retrieval in E-Commerce Search. <strong>PAKDD<\/strong> (2) 2022: 458-471<\/div>\n<div class=\"ace-line ace-line old-record-id-IQ30dYq4mo50OmxdDJcc86fun5g\">[4] Shiyin Lu, Yu-Hang Zhou, Jing-Cheng Shi, Wenya Zhu, Qingtao Yu, Qing-Guo Chen, <strong>Qing Da<\/strong>, Lijun Zhang: Non-stationary Continuum-armed Bandits for Online Hyperparameter Optimization. <strong>WSDM<\/strong> 2022: 618-627<\/div>\n<div class=\"ace-line ace-line old-record-id-GVtFdsO1po8bxnxOPgcce6QLnIc\">[5] Xuesi Wang, Guangda Huzhang, Qianying Lin, <strong>Qing Da<\/strong>: Learning-To-Ensemble by Contextual Rank Aggregation in E-Commerce. <strong>WSDM<\/strong> 2022: 1036-1044<\/div>\n<div class=\"ace-line ace-line old-record-id-DNx5dZTrgoU6eWxhbtlcmzslnWg\">[6] Anxiang Zeng, Han Yu, <strong>Qing Da<\/strong>, Yusen Zhan, Yang Yu, Jingren Zhou, Chunyan Miao: Improving Search Engine Efficiency through Contextual Factor Selection. <strong>AI Mag<\/strong>. 42(2): 50-58 (2021)<\/div>\n<div class=\"ace-line ace-line old-record-id-IpKXd6PvJo6k0gxn7rDcRZubnHW\">[7] Yu-Hang Zhou, Peng Hu, Chen Liang, Huan Xu, Guangda Huzhang, Yinfu Feng, <strong>Qing Da<\/strong>, Xinshang Wang, Anxiang Zeng: A Primal-Dual Online Algorithm for Online Matching Problem in Dynamic Environments. <strong>AAAI<\/strong> 2021: 11160-11167<\/div>\n<div class=\"ace-line ace-line old-record-id-CHImdblAKonXEYxycJJc8w8onJh\">[8] Junmei Hao, Jingcheng Shi, <strong>Qing Da<\/strong>, Anxiang Zeng, Yujie Dun, Xueming Qian, Qianying Lin: Diversity Regularized Interests Modeling for Recommender Systems. CoRR abs\/2103.12404 (2021)<\/div>\n<div class=\"ace-line ace-line old-record-id-B9YAd0rXDoTxoOxLY2acH7Aanlc\">[9] Yongqing Gao, Guangda Huzhang, Weijie Shen, Yawen Liu, Wen-Ji Zhou, <strong>Qing Da<\/strong>, Dan Shen, Yang Yu: Imitate TheWorld: A Search Engine Simulation Platform. CoRR abs\/2107.07693 (2021)<\/div>\n<div class=\"ace-line ace-line old-record-id-ESyBdYnslo6chHxrB5Rc7hjwnie\">[10] Chenlin Shen, Guangda Huzhang, Yu-Hang Zhou, Chen Liang, <strong>Qing D<\/strong>a: A General Traffic Shaping Protocol in E-Commerce. CoRR abs\/2112.14941 (2021)<\/div>\n<div><\/div>\n<p>&nbsp;<\/p>\n<h3 class=\"ace-line ace-line old-record-id-IJfqduP5uoBc0xxiaGrcPUgsnXg\">2020<\/h3>\n<div class=\"ace-line ace-line old-record-id-N8kTdF9E9oIuNLx4dgXcSlvsnQg\">[1] Anxiang Zeng, Han Yu, <strong>Qing Da<\/strong>, Yusen Zhan, Chunyan Miao: Accelerating Ranking in E-Commerce Search Engines through Contextual Factor Selection. <strong>AAAI<\/strong> 2020: 13212-13219<\/div>\n<div class=\"ace-line ace-line old-record-id-KxSwdoWWZozPaMxzdFOcWKgOndh\">[2] Pengcheng Li, Runze Li, <strong>Qing Da<\/strong>, Anxiang Zeng, Lijun Zhang: Improving Multi-Scenario Learning to Rank in E-commerce by Exploiting Task Relationships in the Label Space. <strong>CIKM<\/strong> 2020: 2605-2612<\/div>\n<div class=\"ace-line ace-line old-record-id-XEFcd7mBEoWWIgxXiXVc6aLgnxg\">[3] Guangda Huzhang, Zhen-Jia Pang, Yongqing Gao, Wen-Ji Zhou, <strong>Qing Da<\/strong>, Anxiang Zeng, Yang Yu: Validation Set Evaluation can be Wrong: An Evaluator-Generator Approach for Maximizing Online Performance of Ranking in E-commerce. CoRR abs\/2003.11941 (2020)<\/div>\n<div class=\"ace-line ace-line old-record-id-CacLdhmz8o7fsbxqjUVcf2dQnvh\">[4] Yanshi Wang, Jie Zhang, <strong>Qing D<\/strong>a, Anxiang Zeng: Delayed Feedback Modeling for the Entire Space Conversion Rate Prediction. CoRR abs\/2011.11826 (2020)<\/div>\n<div><\/div>\n<p>&nbsp;<\/p>\n<h3 class=\"ace-line ace-line old-record-id-IzY6d0LySokb2dxvkU9cgbeEnvb\">2019<\/h3>\n<div class=\"ace-line ace-line old-record-id-K2bldpC4WodWcnxUzVucOimqnxh\">[1] Feiyang Pan, Qingpeng Cai, Anxiang Zeng, Chun-Xiang Pan, <strong>Qing Da<\/strong>, Hua-Lin He, Qing He, Pingzhong Tang: Policy Optimization with Model-Based Explorations. <strong>AAAI<\/strong> 2019: 4675-4682<\/div>\n<div class=\"ace-line ace-line old-record-id-WzGCdpV7jo1Mw0xK0wfc1SONnSd\">[2] Jing-Cheng Shi, Yang Yu, <strong>Qing Da<\/strong>, Shi-Yong Chen, Anxiang Zeng: Virtual-Taobao: Virtualizing Real-World Online Retail Environment for Reinforcement Learning. <strong>AAAI<\/strong> 2019: 4902-4909<\/div>\n<div><\/div>\n<p>&nbsp;<\/p>\n<h3 class=\"ace-line ace-line old-record-id-KqEsdHnKAo0FzXx9lGRci7KonKh\">2018<\/h3>\n<div class=\"ace-line ace-line old-record-id-GUmVdEhovonBwuxTnFBcDF7un6b\">[1] Yang Yu, Shi-Yong Chen, <strong>Qing Da<\/strong>, Zhi-Hua Zhou: Reusable Reinforcement Learning via Shallow Trails. <strong>IEEE Trans. Neural Networks Learn. Syst<\/strong>. 29(6): 2204-2215 (2018)<\/div>\n<div class=\"ace-line ace-line old-record-id-J8igdNyA5o1sUSxeGO7c4MpgnNb\">[2] Yujing Hu, <strong>Qing Da<\/strong>, Anxiang Zeng, Yang Yu, Yinghui Xu: Reinforcement Learning to Rank in E-Commerce Search Engine: Formalization, Analysis, and Application. <strong>KDD<\/strong> 2018: 368-377<\/div>\n<div class=\"ace-line ace-line old-record-id-FHSqdrx9RoxWjIxXzcEc07DCnHf\">[3] Shi-Yong Chen, Yang Yu, <strong>Qing Da<\/strong>, Jun Tan, Hai-Kuan Huang, Hai-Hong Tang: Stabilizing Reinforcement Learning in Dynamic Environment with Application to Online Recommendation. <strong>KDD<\/strong> 2018: 1187-1196<\/div>\n<div class=\"ace-line ace-line old-record-id-HQ2MdBVRoooqn8x0GvWc8pCln0e\">[4] Hua-Lin He, Chun-Xiang Pan, <strong>Qing Da<\/strong>, Anxiang Zeng: SPEEDING Up the Metabolism in E-commerce by Reinforcement Mechanism DESIGN. <strong>ECML\/PKDD<\/strong> (3) 2018: 105-119<\/div>\n<div><\/div>\n<p>&nbsp;<\/p>\n<h3 class=\"ace-line ace-line old-record-id-WtypdVZNKoVOFKxTLwyco5VLnge\">2016<\/h3>\n<div class=\"ace-line ace-line old-record-id-OEt5dVlBtoAv4hxWmACc7sPRnr9\">[1] Yang Yu, Peng-Fei Hou, <strong>Qing Da<\/strong>, Yu Qian: Boosting Nonparametric Policies. <strong>AAMAS<\/strong> 2016: 477-484<\/div>\n<div class=\"ace-line ace-line old-record-id-OcbodXmyQomu8HxgPeocuZYanQh\">2014<\/div>\n<div class=\"ace-line ace-line old-record-id-FbmsdUPIvoR9ZOxJdZAchnQHnde\">[2] <strong>Qing Da<\/strong>, Yang Yu, Zhi-Hua Zhou: Learning with Augmented Class by Exploiting Unlabeled Data. <strong>AAAI<\/strong> 2014: 1760-1766<\/div>\n<div class=\"ace-line ace-line old-record-id-F1y2dtGT5oE2Nrx8nBmc7YwMnjc\">[3] <strong>Qing Da<\/strong>, Yang Yu, Zhi-Hua Zhou: Napping for functional representation of policy. <strong>AAMAS<\/strong> 2014: 189-196<\/div>\n<div class=\"ace-line ace-line old-record-id-UN62dtl1CowxKXxeUsNcYYqLnhf\">2013<\/div>\n<div class=\"ace-line ace-line old-record-id-TgljdhpdZoOXlixQdfAcPlQdnMP\">[4] <strong>Qing Da<\/strong>, Yang Yu, Zhi-Hua Zhou: Self-Practice Imitation Learning from Weak Policy. <strong>PSL<\/strong> 2013: 9-20<\/div>\n<\/div>\n","protected":false},"excerpt":{"rendered":"<p>E-mail \/ Google scholar \/ DBLP \/ \u4e2d\u6587\u7248 Formerly a Senior  [&hellip;]<\/p>\n","protected":false},"author":1,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":[],"_links":{"self":[{"href":"http:\/\/daqings.net\/index.php?rest_route=\/wp\/v2\/pages\/10"}],"collection":[{"href":"http:\/\/daqings.net\/index.php?rest_route=\/wp\/v2\/pages"}],"about":[{"href":"http:\/\/daqings.net\/index.php?rest_route=\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"http:\/\/daqings.net\/index.php?rest_route=\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"http:\/\/daqings.net\/index.php?rest_route=%2Fwp%2Fv2%2Fcomments&post=10"}],"version-history":[{"count":39,"href":"http:\/\/daqings.net\/index.php?rest_route=\/wp\/v2\/pages\/10\/revisions"}],"predecessor-version":[{"id":89,"href":"http:\/\/daqings.net\/index.php?rest_route=\/wp\/v2\/pages\/10\/revisions\/89"}],"wp:attachment":[{"href":"http:\/\/daqings.net\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=10"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}