{"id":29922,"date":"2023-12-14T14:57:20","date_gmt":"2023-12-14T13:57:20","guid":{"rendered":"https:\/\/www.l3s.de\/?p=29922"},"modified":"2023-12-14T14:57:24","modified_gmt":"2023-12-14T13:57:24","slug":"l3s-researchers-receive-icdm-2023-best-paper-award","status":"publish","type":"post","link":"https:\/\/www.l3s.de\/de\/l3s-researchers-receive-icdm-2023-best-paper-award\/","title":{"rendered":"L3S Researchers receive ICDM 2023 Best Paper Award"},"content":{"rendered":"<p class=\"wp-block-paragraph\">L3S Researchers have received the Best Paper Award at this year\u2019s <a href=\"https:\/\/www.cloud-conf.net\/icdm2023\/\" target=\"_blank\" rel=\"noopener\" title=\"IEEE International Conference on Data Mining (ICDM) \">IEEE International Conference on Data Mining (ICDM) <\/a>for their paper &#8220;A Deep Reinforcement Learning Approach to Configuration Sampling Problem&#8221;.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">\u201cConfiguration sampling is a complex problem involving finding a minimal subset of configurations that includes all possible t-wise combinations of features. We introduced a new method called RLSampler that uses deep reinforcement learning to achieve this, ensuring 100% coverage with fewer configurations compared to state-of-the art heuristic methods\u201d, says Amir Abolfazli, one of the authors of the paper. \u201cOur tests on eight real-world feature models of software product lines demonstrated that our approach performs much better than heuristic-based methods, meaning we need fewer configurations to test. This reduction in testing size leads to cost savings by requiring less effort, resources, and time for testing\u201d explains Amir Abolfazli further.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">The ICDM took place from Dec. 1 \u2013 Dec. 4, 2023. It is widely regarded as the leading research conference in the field. The ICDM is a forum for presenting original research, sharing innovative development experiences, and facilitating the exchange of ideas in the field of data mining. The conference covers a wide range of topics, including algorithms, software, systems, and applications. Big data, deep learning, pattern recognition, statistical and machine learning, databases, data warehousing, data visualization, knowledge-based systems, and high-performance computing are all represented at ICDM. The conference aims to advance the field&#8217;s state-of-the-art by showcasing novel research and creative solutions to data mining challenges.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Many congratulations to our colleagues for this recognition!<\/p>","protected":false},"excerpt":{"rendered":"<p>L3S Researchers have received the Best Paper Award at this year\u2019s IEEE International Conference on Data Mining (ICDM) for their paper &#8220;A Deep Reinforcement Learning Approach to Configuration Sampling Problem&#8221;. \u201cConfiguration sampling is a complex problem involving finding a minimal subset of configurations that includes all possible t-wise combinations of features. We introduced a new [&hellip;]<\/p>\n","protected":false},"author":5,"featured_media":29923,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"footnotes":""},"categories":[10],"tags":[],"class_list":["post-29922","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-news"],"acf":[],"aioseo_notices":[],"aioseo_head":"\n\t\t<!-- All in One SEO 4.9.8 - aioseo.com -->\n\t<meta name=\"description\" content=\"L3S Researchers have received the Best Paper Award at this year\u2019s ICDM for their paper &quot;A Deep Reinforcement Learning Approach to Configuration Sampling Problem\" \/>\n\t<meta name=\"robots\" content=\"max-image-preview:large\" \/>\n\t<meta name=\"author\" content=\"Sophie Bone\u00df\"\/>\n\t<link rel=\"canonical\" href=\"https:\/\/www.l3s.de\/de\/l3s-researchers-receive-icdm-2023-best-paper-award\/\" \/>\n\t<meta name=\"generator\" content=\"All in One SEO 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