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In this article, we present a new framework for graph-based semi-supervised learning. We present a powerful method for simultaneous label inference and linear transform estimation. The targeted linear transformation is used to obtain a discriminant subspace. To improve semi-supervised learning, our framework focuses on exploiting the data structure and soft labels of the available unlabeled samples. In the iterative optimization scheme used, the prior estimation of the label increases the supervision information indirectly through an introduced informative matrix called the label graph, thus avoiding the use of hard confidence-based decisions as used in self-supervised methods. In addition, the estimation of labels and projected data is made more robust by using smoothing concepts based on hybrid graphs. For each type of smoothing, the hybrid graph is an adaptive fusion of the two graphs encoding the similarity of the data and the similarity of the labels. The proposed method leads to an improved discriminative linear transformation. Several experimental results on real image datasets confirm the effectiveness of the proposed method. They also show superior performance compared to semi-supervised methods that use integration and label inference simultaneously.<\/jats:p>","DOI":"10.1145\/3590172","type":"journal-article","created":{"date-parts":[[2023,4,22]],"date-time":"2023-04-22T11:01:44Z","timestamp":1682161304000},"page":"1-25","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":3,"title":["Joint Latent Space and Label Inference Estimation with Adaptive Fused Data and Label Graphs"],"prefix":"10.1145","volume":"14","author":[{"ORCID":"https:\/\/orcid.org\/0009-0002-8451-369X","authenticated-orcid":false,"given":"A.","family":"Baradaaji","sequence":"first","affiliation":[{"name":"University of the Basque Country UPV\/EHU, San Sebastian, Spain"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6581-9680","authenticated-orcid":false,"given":"F.","family":"Dornaika","sequence":"additional","affiliation":[{"name":"University of the Basque Country UPV\/EHU, San Sebastian, Spain, and Ho Chi Minh City Open University, Ho Chi Minh City, Vietnam"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"320","published-online":{"date-parts":[[2023,6,15]]},"reference":[{"key":"e_1_3_2_2_2","doi-asserted-by":"publisher","DOI":"10.5555\/1248547.1248632"},{"key":"e_1_3_2_3_2","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2007.4408856"},{"key":"e_1_3_2_4_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.ins.2020.07.065"},{"key":"e_1_3_2_5_2","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2021.3057270"},{"key":"e_1_3_2_6_2","doi-asserted-by":"publisher","DOI":"10.1109\/TCYB.2015.2399456"},{"key":"e_1_3_2_7_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.patcog.2016.07.029"},{"key":"e_1_3_2_8_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.neunet.2019.03.002"},{"key":"e_1_3_2_9_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2015.04.042"},{"key":"e_1_3_2_10_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.knosys.2021.106809"},{"key":"e_1_3_2_11_2","doi-asserted-by":"crossref","unstructured":"Fang He Feiping Nie Rong Wang Weimin Jia Fenggan Zhang and Xuelong Li. 2020. 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