{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,9,29]],"date-time":"2025-09-29T20:53:10Z","timestamp":1759179190617,"version":"3.44.0"},"publisher-location":"New York, NY, USA","reference-count":18,"publisher":"ACM","license":[{"start":{"date-parts":[[2023,10,27]],"date-time":"2023-10-27T00:00:00Z","timestamp":1698364800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"funder":[{"DOI":"10.13039\/501100006374","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["62102442"],"award-info":[{"award-number":["62102442"]}],"id":[{"id":"10.13039\/501100006374","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2023,10,27]]},"DOI":"10.1145\/3635638.3635663","type":"proceedings-article","created":{"date-parts":[[2024,1,16]],"date-time":"2024-01-16T18:43:15Z","timestamp":1705430595000},"page":"171-177","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":2,"title":["Swarm GAN: Stabilizing Training of Generative Adversarial Networks via Swarm Intelligence"],"prefix":"10.1145","author":[{"ORCID":"https:\/\/orcid.org\/0009-0009-8815-2407","authenticated-orcid":false,"given":"Zihao","family":"Li","sequence":"first","affiliation":[{"name":"Research and Development Department, Intelligent Game and Decision Lab (IGDL), China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3103-5535","authenticated-orcid":false,"given":"Yuan","family":"Zhou","sequence":"additional","affiliation":[{"name":"Research and Development Department, Intelligent Game and Decision Lab (IGDL), China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0003-9592-7625","authenticated-orcid":false,"given":"Zhiyuan","family":"Wang","sequence":"additional","affiliation":[{"name":"Research and Development Department, Intelligent Game and Decision Lab (IGDL), China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0004-4768-9164","authenticated-orcid":false,"given":"Minne","family":"Li","sequence":"additional","affiliation":[{"name":"Research and Development Department, Intelligent Game and Decision Lab (IGDL), China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","published-online":{"date-parts":[[2024,1,16]]},"reference":[{"key":"e_1_3_2_1_1_1","volume-title":"International conference on machine learning. PMLR, 214\u2013223","author":"Arjovsky Martin","year":"2017","unstructured":"Martin Arjovsky, Soumith Chintala, and L\u00e9on Bottou. 2017. Wasserstein generative adversarial networks. In International conference on machine learning. PMLR, 214\u2013223."},{"key":"e_1_3_2_1_2_1","volume-title":"Large scale GAN training for high fidelity natural image synthesis. arXiv preprint arXiv:1809.11096","author":"Brock Andrew","year":"2018","unstructured":"Andrew Brock, Jeff Donahue, and Karen Simonyan. 2018. Large scale GAN training for high fidelity natural image synthesis. arXiv preprint arXiv:1809.11096 (2018)."},{"key":"e_1_3_2_1_3_1","volume-title":"Advances in Neural Information Processing Systems, D.\u00a0Lee, M.\u00a0Sugiyama, U.\u00a0Luxburg, I.\u00a0Guyon, and R.\u00a0Garnett (Eds.). Vol.\u00a029. Curran Associates","author":"Chen Xi","year":"2016","unstructured":"Xi Chen, Yan Duan, Rein Houthooft, John Schulman, Ilya Sutskever, and Pieter Abbeel. 2016. InfoGAN: Interpretable Representation Learning by Information Maximizing Generative Adversarial Nets. In Advances in Neural Information Processing Systems, D.\u00a0Lee, M.\u00a0Sugiyama, U.\u00a0Luxburg, I.\u00a0Guyon, and R.\u00a0Garnett (Eds.). Vol.\u00a029. Curran Associates, Inc.https:\/\/proceedings.neurips.cc\/paper_files\/paper\/2016\/file\/7c9d0b1f96aebd7b5eca8c3edaa19ebb-Paper.pdf"},{"key":"e_1_3_2_1_4_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.patcog.2021.108098"},{"key":"e_1_3_2_1_5_1","volume-title":"Generative adversarial nets. Advances in neural information processing systems 27","author":"Goodfellow Ian","year":"2014","unstructured":"Ian Goodfellow, Jean Pouget-Abadie, Mehdi Mirza, Bing Xu, David Warde-Farley, Sherjil Ozair, Aaron Courville, and Yoshua Bengio. 2014. Generative adversarial nets. Advances in neural information processing systems 27 (2014)."},{"key":"e_1_3_2_1_6_1","volume-title":"Improved training of wasserstein gans. Advances in neural information processing systems 30","author":"Gulrajani Ishaan","year":"2017","unstructured":"Ishaan Gulrajani, Faruk Ahmed, Martin Arjovsky, Vincent Dumoulin, and Aaron\u00a0C Courville. 2017. Improved training of wasserstein gans. Advances in neural information processing systems 30 (2017)."},{"key":"e_1_3_2_1_7_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR46437.2021.00091"},{"key":"e_1_3_2_1_8_1","unstructured":"Qunwei Li Bhavya Kailkhura Rushil Anirudh Yi Zhou Yingbin Liang and Pramod Varshney. 2018. MR-GAN: Manifold Regularized Generative Adversarial Networks. arxiv:1811.10427\u00a0[cs.LG]"},{"key":"e_1_3_2_1_9_1","unstructured":"Mehdi Mirza and Simon Osindero. 2014. Conditional Generative Adversarial Nets. arxiv:1411.1784\u00a0[cs.LG]"},{"key":"e_1_3_2_1_10_1","unstructured":"Takeru Miyato Toshiki Kataoka Masanori Koyama and Yuichi Yoshida. 2018. Spectral Normalization for Generative Adversarial Networks. arxiv:1802.05957\u00a0[cs.LG]"},{"key":"e_1_3_2_1_11_1","volume-title":"Unsupervised representation learning with deep convolutional generative adversarial networks. arXiv preprint arXiv:1511.06434","author":"Radford Alec","year":"2015","unstructured":"Alec Radford, Luke Metz, and Soumith Chintala. 2015. Unsupervised representation learning with deep convolutional generative adversarial networks. arXiv preprint arXiv:1511.06434 (2015)."},{"key":"e_1_3_2_1_12_1","volume-title":"Advances in Neural Information Processing Systems, D.\u00a0Lee, M.\u00a0Sugiyama, U.\u00a0Luxburg, I.\u00a0Guyon, and R.\u00a0Garnett (Eds.). Vol.\u00a029. Curran Associates","author":"Salimans Tim","year":"2016","unstructured":"Tim Salimans, Ian Goodfellow, Wojciech Zaremba, Vicki Cheung, Alec Radford, Xi Chen, and Xi Chen. 2016. Improved Techniques for Training GANs. In Advances in Neural Information Processing Systems, D.\u00a0Lee, M.\u00a0Sugiyama, U.\u00a0Luxburg, I.\u00a0Guyon, and R.\u00a0Garnett (Eds.). Vol.\u00a029. Curran Associates, Inc.https:\/\/proceedings.neurips.cc\/paper_files\/paper\/2016\/file\/8a3363abe792db2d8761d6403605aeb7-Paper.pdf"},{"key":"e_1_3_2_1_13_1","doi-asserted-by":"publisher","DOI":"10.12720\/jait.13.5.456-461"},{"key":"e_1_3_2_1_14_1","doi-asserted-by":"publisher","DOI":"10.1109\/TEVC.2019.2895748"},{"key":"e_1_3_2_1_15_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52688.2022.01109"},{"key":"e_1_3_2_1_16_1","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v31i1.10804"},{"key":"e_1_3_2_1_17_1","volume-title":"Proceedings of the 36th International Conference on Machine Learning(Proceedings of Machine Learning Research, Vol.\u00a097)","author":"Zhang Han","year":"2019","unstructured":"Han Zhang, Ian Goodfellow, Dimitris Metaxas, and Augustus Odena. 2019. Self-Attention Generative Adversarial Networks. In Proceedings of the 36th International Conference on Machine Learning(Proceedings of Machine Learning Research, Vol.\u00a097), Kamalika Chaudhuri and Ruslan Salakhutdinov (Eds.). PMLR, 7354\u20137363. https:\/\/proceedings.mlr.press\/v97\/zhang19d.html"},{"key":"e_1_3_2_1_18_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.future.2021.03.022"}],"event":{"name":"MLMI 2023: The 6th International Conference on Machine Learning and Machine Intelligence","acronym":"MLMI 2023","location":"Chongqing China"},"container-title":["The 6th International Conference on Machine Learning and Machine Intelligence"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3635638.3635663","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3635638.3635663","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,8,26]],"date-time":"2025-08-26T19:54:08Z","timestamp":1756238048000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3635638.3635663"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,10,27]]},"references-count":18,"alternative-id":["10.1145\/3635638.3635663","10.1145\/3635638"],"URL":"https:\/\/doi.org\/10.1145\/3635638.3635663","relation":{},"subject":[],"published":{"date-parts":[[2023,10,27]]},"assertion":[{"value":"2024-01-16","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}