{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,17]],"date-time":"2026-02-17T03:40:22Z","timestamp":1771299622404,"version":"3.50.1"},"publisher-location":"California","reference-count":0,"publisher":"International Joint Conferences on Artificial Intelligence Organization","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2023,8]]},"abstract":"<jats:p>Dataset distillation is attracting more attention in machine learning as training sets continue to grow and the cost of training state-of-the-art models becomes increasingly high. By synthesizing datasets with high information density, dataset distillation offers a range of potential applications, including support for continual learning, neural architecture search, and privacy protection. Despite recent advances, we lack a holistic understanding of the approaches and applications. Our survey aims to bridge this gap by first proposing a taxonomy of dataset distillation, characterizing existing approaches, and then systematically reviewing the data modalities, and related applications. In addition, we summarize the challenges and discuss future directions for this field of research.<\/jats:p>","DOI":"10.24963\/ijcai.2023\/741","type":"proceedings-article","created":{"date-parts":[[2023,8,11]],"date-time":"2023-08-11T04:31:30Z","timestamp":1691728290000},"page":"6610-6618","source":"Crossref","is-referenced-by-count":15,"title":["A Survey on Dataset Distillation: Approaches, Applications and Future Directions"],"prefix":"10.24963","author":[{"given":"Jiahui","family":"Geng","sequence":"first","affiliation":[{"name":"University of Stavanger"}]},{"given":"Zongxiong","family":"Chen","sequence":"additional","affiliation":[{"name":"Fraunhofer FOKUS"}]},{"given":"Yuandou","family":"Wang","sequence":"additional","affiliation":[{"name":"University of Amsterdam"}]},{"given":"Herbert","family":"Woisetschlaeger","sequence":"additional","affiliation":[{"name":"Technical University of Munich"}]},{"given":"Sonja","family":"Schimmler","sequence":"additional","affiliation":[{"name":"Fraunhofer FOKUS"}]},{"given":"Ruben","family":"Mayer","sequence":"additional","affiliation":[{"name":"Technical University of Munich"}]},{"given":"Zhiming","family":"Zhao","sequence":"additional","affiliation":[{"name":"University of Amsterdam"}]},{"given":"Chunming","family":"Rong","sequence":"additional","affiliation":[{"name":"University of Stavanger"}]}],"member":"10584","event":{"name":"Thirty-Second International Joint Conference on Artificial Intelligence {IJCAI-23}","theme":"Artificial Intelligence","location":"Macau, SAR China","acronym":"IJCAI-2023","number":"32","sponsor":["International Joint Conferences on Artificial Intelligence Organization (IJCAI)"],"start":{"date-parts":[[2023,8,19]]},"end":{"date-parts":[[2023,8,25]]}},"container-title":["Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence"],"original-title":[],"deposited":{"date-parts":[[2023,8,11]],"date-time":"2023-08-11T04:55:01Z","timestamp":1691729701000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.ijcai.org\/proceedings\/2023\/741"}},"subtitle":[],"proceedings-subject":"Artificial Intelligence Research Articles","short-title":[],"issued":{"date-parts":[[2023,8]]},"references-count":0,"URL":"https:\/\/doi.org\/10.24963\/ijcai.2023\/741","relation":{},"subject":[],"published":{"date-parts":[[2023,8]]}}}