{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,5]],"date-time":"2025-10-05T20:00:43Z","timestamp":1759694443442},"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":[[2017,8]]},"abstract":"<jats:p>Supervised topic models leverage label information to learn discriminative latent topic representations. As collecting a fully labeled dataset is often time-consuming, semi-supervised learning is of high interest. In this paper, we present an effective semi-supervised max-margin topic model by naturally introducing manifold posterior regularization to a regularized Bayesian topic model, named LapMedLDA. The model jointly learns latent topics and a related classifier with only a small fraction of labeled documents. To perform the approximate inference, we derive an efficient stochastic gradient MCMC method. Unlike the previous semi-supervised topic models, our model adopts a tight coupling between the generative topic model and the discriminative classifier. Extensive experiments demonstrate that such tight coupling brings significant benefits in quantitative and qualitative performance.<\/jats:p>","DOI":"10.24963\/ijcai.2017\/259","type":"proceedings-article","created":{"date-parts":[[2017,7,28]],"date-time":"2017-07-28T05:14:07Z","timestamp":1501218847000},"page":"1865-1871","source":"Crossref","is-referenced-by-count":5,"title":["Semi-supervised Max-margin Topic Model with Manifold Posterior Regularization"],"prefix":"10.24963","author":[{"given":"Wenbo","family":"Hu","sequence":"first","affiliation":[{"name":"Tsinghua National Laboratory for Information Science and Technology (TNList)"},{"name":"State Key Lab for Intelligent Technology and Systems"},{"name":"Center for Brain-Inspired Computing Research (CBICR)"},{"name":"Department of Computer Science and Technology, Tsinghua University, Beijing, 100084, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jun","family":"Zhu","sequence":"additional","affiliation":[{"name":"Tsinghua National Laboratory for Information Science and Technology (TNList)"},{"name":"State Key Lab for Intelligent Technology and Systems"},{"name":"Center for Brain-Inspired Computing Research (CBICR)"},{"name":"Department of Computer Science and Technology, Tsinghua University, Beijing, 100084, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hang","family":"Su","sequence":"additional","affiliation":[{"name":"Tsinghua National Laboratory for Information Science and Technology (TNList)"},{"name":"State Key Lab for Intelligent Technology and Systems"},{"name":"Center for Brain-Inspired Computing Research (CBICR)"},{"name":"Department of Computer Science and Technology, Tsinghua University, Beijing, 100084, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jingwei","family":"Zhuo","sequence":"additional","affiliation":[{"name":"Tsinghua National Laboratory for Information Science and Technology (TNList)"},{"name":"State Key Lab for Intelligent Technology and Systems"},{"name":"Center for Brain-Inspired Computing Research (CBICR)"},{"name":"Department of Computer Science and Technology, Tsinghua University, Beijing, 100084, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Bo","family":"Zhang","sequence":"additional","affiliation":[{"name":"Tsinghua National Laboratory for Information Science and Technology (TNList)"},{"name":"State Key Lab for Intelligent Technology and Systems"},{"name":"Center for Brain-Inspired Computing Research (CBICR)"},{"name":"Department of Computer Science and Technology, Tsinghua University, Beijing, 100084, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"10584","event":{"number":"26","sponsor":["International Joint Conferences on Artificial Intelligence Organization (IJCAI)","University of Technology Sydney (UTS)","Australian Computer Society (ACS)"],"acronym":"IJCAI-2017","name":"Twenty-Sixth International Joint Conference on Artificial Intelligence","start":{"date-parts":[[2017,8,19]]},"theme":"Artificial Intelligence","location":"Melbourne, Australia","end":{"date-parts":[[2017,8,26]]}},"container-title":["Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence"],"original-title":[],"deposited":{"date-parts":[[2017,7,28]],"date-time":"2017-07-28T07:53:03Z","timestamp":1501228383000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.ijcai.org\/proceedings\/2017\/259"}},"subtitle":[],"proceedings-subject":"Artificial Intelligence Research Articles","short-title":[],"issued":{"date-parts":[[2017,8]]},"references-count":0,"URL":"https:\/\/doi.org\/10.24963\/ijcai.2017\/259","relation":{},"subject":[],"published":{"date-parts":[[2017,8]]}}}