{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,6,18]],"date-time":"2025-06-18T04:21:25Z","timestamp":1750220485065,"version":"3.41.0"},"publisher-location":"New York, NY, USA","reference-count":50,"publisher":"ACM","license":[{"start":{"date-parts":[[2021,10,18]],"date-time":"2021-10-18T00:00:00Z","timestamp":1634515200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2021,10,18]]},"DOI":"10.1145\/3461615.3486575","type":"proceedings-article","created":{"date-parts":[[2021,12,18]],"date-time":"2021-12-18T04:57:40Z","timestamp":1639803460000},"page":"317-323","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":2,"title":["Addressing Data Scarcity in Multimodal User State Recognition by Combining Semi-Supervised and Supervised Learning"],"prefix":"10.1145","author":[{"given":"Hendric","family":"Vo\u00df","sequence":"first","affiliation":[{"name":"Social Cognitive Systems Group, Bielefeld University, Germany"}]},{"given":"Heiko","family":"Wersing","sequence":"additional","affiliation":[{"name":"Honda Research Institute Europe, Germany"}]},{"given":"Stefan","family":"Kopp","sequence":"additional","affiliation":[{"name":"Bielefeld University, Germany"}]}],"member":"320","published-online":{"date-parts":[[2021,12,17]]},"reference":[{"key":"e_1_3_2_1_1_1","doi-asserted-by":"crossref","unstructured":"S. Amari N. Murata K. M\u00fcller M. Finke and H. Yang. 1997. Asymptotic statistical theory of overtraining and cross-validation. IEEE transactions on neural networks 8 5 (1997) 985\u201396.  S. Amari N. Murata K. M\u00fcller M. Finke and H. Yang. 1997. Asymptotic statistical theory of overtraining and cross-validation. IEEE transactions on neural networks 8 5 (1997) 985\u201396.","DOI":"10.1109\/72.623200"},{"key":"e_1_3_2_1_2_1","doi-asserted-by":"publisher","DOI":"10.1080\/713756728"},{"key":"e_1_3_2_1_3_1","volume-title":"International conference on machine learning. PMLR, 115\u2013123","author":"Bergstra James","year":"2013","unstructured":"James Bergstra , Daniel Yamins , and David Cox . 2013 . Making a science of model search: Hyperparameter optimization in hundreds of dimensions for vision architectures . In International conference on machine learning. PMLR, 115\u2013123 . James Bergstra, Daniel Yamins, and David Cox. 2013. Making a science of model search: Hyperparameter optimization in hundreds of dimensions for vision architectures. In International conference on machine learning. PMLR, 115\u2013123."},{"key":"e_1_3_2_1_4_1","doi-asserted-by":"publisher","DOI":"10.1109\/ACIIW.2019.8925037"},{"key":"e_1_3_2_1_5_1","doi-asserted-by":"publisher","DOI":"10.1109\/FG.2011.5771341"},{"key":"e_1_3_2_1_6_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2017.116"},{"key":"e_1_3_2_1_7_1","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/W19-2306"},{"key":"e_1_3_2_1_8_1","doi-asserted-by":"publisher","DOI":"10.1109\/TASLP.2019.2938863"},{"key":"e_1_3_2_1_9_1","volume-title":"Proceedings of the 25th Annual Penn Linguistics Colloquium 8, 1(2003)","author":"Cohen Shuki","year":"2003","unstructured":"Shuki Cohen . 2003 . A computerized scale for monitoring levels of agreement during a conversation . Proceedings of the 25th Annual Penn Linguistics Colloquium 8, 1(2003) , 57\u201370. Shuki Cohen. 2003. A computerized scale for monitoring levels of agreement during a conversation. Proceedings of the 25th Annual Penn Linguistics Colloquium 8, 1(2003), 57\u201370."},{"key":"e_1_3_2_1_10_1","unstructured":"Stephen Colbert. [n.d.]. The Late Show with Stephen Colbert - Youtube. https:\/\/www.youtube.com\/channel\/UCMtFAi84ehTSYSE9XoHefig. (Accessed on 08\/20\/2020).  Stephen Colbert. [n.d.]. The Late Show with Stephen Colbert - Youtube. https:\/\/www.youtube.com\/channel\/UCMtFAi84ehTSYSE9XoHefig. (Accessed on 08\/20\/2020)."},{"key":"e_1_3_2_1_11_1","unstructured":"James Corden. [n.d.]. The Late Late Show with James Corden - Youtube. https:\/\/www.youtube.com\/user\/TheLateLateShow. (Accessed on 08\/20\/2020).  James Corden. [n.d.]. The Late Late Show with James Corden - Youtube. https:\/\/www.youtube.com\/user\/TheLateLateShow. (Accessed on 08\/20\/2020)."},{"key":"e_1_3_2_1_12_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPRW50498.2020.00359"},{"key":"e_1_3_2_1_13_1","volume-title":"Simple and effective semi-supervised question answering. arXiv","author":"Dhingra Bhuwan","year":"2018","unstructured":"Bhuwan Dhingra , Danish Pruthi , and Dheeraj Rajagopal . 2018. Simple and effective semi-supervised question answering. arXiv ( 2018 ), 582\u2013587. Bhuwan Dhingra, Danish Pruthi, and Dheeraj Rajagopal. 2018. Simple and effective semi-supervised question answering. arXiv (2018), 582\u2013587."},{"key":"e_1_3_2_1_14_1","unstructured":"Alan\u00a0M. Dunn Owen\u00a0S. Hofmann Brent Waters and Emmett Witchel. 2011. Cloaking malware with the trusted platform module. 395\u2013410\u00a0pages.  Alan\u00a0M. Dunn Owen\u00a0S. Hofmann Brent Waters and Emmett Witchel. 2011. Cloaking malware with the trusted platform module. 395\u2013410\u00a0pages."},{"key":"e_1_3_2_1_15_1","doi-asserted-by":"publisher","DOI":"10.3115\/1218955.1219040"},{"key":"e_1_3_2_1_16_1","volume-title":"Res2net: A new multi-scale backbone architecture","author":"Gao Shanghua","year":"2019","unstructured":"Shanghua Gao , Ming-Ming Cheng , Kai Zhao , Xin-Yu Zhang , Ming-Hsuan Yang , and Philip\u00a0 HS Torr . 2019. Res2net: A new multi-scale backbone architecture . IEEE transactions on pattern analysis and machine intelligence ( 2019 ). Shanghua Gao, Ming-Ming Cheng, Kai Zhao, Xin-Yu Zhang, Ming-Hsuan Yang, and Philip\u00a0HS Torr. 2019. Res2net: A new multi-scale backbone architecture. IEEE transactions on pattern analysis and machine intelligence (2019)."},{"key":"e_1_3_2_1_17_1","doi-asserted-by":"publisher","DOI":"10.1145\/3375462.3375485"},{"key":"e_1_3_2_1_18_1","doi-asserted-by":"publisher","DOI":"10.1145\/1647314.1647319"},{"key":"e_1_3_2_1_19_1","volume-title":"Exploiting Unlabeled Data using Contrast Classifiers. Computational LinguisticsJune","author":"Hahn Sangyun","year":"2006","unstructured":"Sangyun Hahn , Richard Ladner , and Mari Ostendorf . 2006. Agreement \/ Disagreement Classification : Exploiting Unlabeled Data using Contrast Classifiers. Computational LinguisticsJune ( 2006 ), 53\u201356. Sangyun Hahn, Richard Ladner, and Mari Ostendorf. 2006. Agreement \/ Disagreement Classification : Exploiting Unlabeled Data using Contrast Classifiers. Computational LinguisticsJune (2006), 53\u201356."},{"volume-title":"Proceedings of the 2003 Conference of the North American","author":"Hillard Dustin","key":"e_1_3_2_1_20_1","unstructured":"Dustin Hillard , Mari Ostendorf , and Elizabeth Shriberg . 2003. Detection of agreement vs. disagreement in meetings . In Proceedings of the 2003 Conference of the North American Chapter of the Association for Computational Linguistics on Human Language Technology companion volume of the Proceedings of HLT-NAACL 2003\u2013short papers - NAACL \u201903, Vol.\u00a02. Association for Computational Linguistics , Morristown, NJ, USA, 34\u201336. https:\/\/doi.org\/10.3115\/1073483.1073495 Dustin Hillard, Mari Ostendorf, and Elizabeth Shriberg. 2003. Detection of agreement vs. disagreement in meetings. In Proceedings of the 2003 Conference of the North American Chapter of the Association for Computational Linguistics on Human Language Technology companion volume of the Proceedings of HLT-NAACL 2003\u2013short papers - NAACL \u201903, Vol.\u00a02. Association for Computational Linguistics, Morristown, NJ, USA, 34\u201336. https:\/\/doi.org\/10.3115\/1073483.1073495"},{"key":"e_1_3_2_1_21_1","volume-title":"2017 7th International Conference on Affective Computing and Intelligent Interaction Workshops and Demos, ACIIW 2017 2018-Janua (2018","author":"Hiray Sushant","year":"2018","unstructured":"Sushant Hiray and Venkatesh Duppada . 2018 . Agree to disagree: Improving disagreement detection with dual GRUs . 2017 7th International Conference on Affective Computing and Intelligent Interaction Workshops and Demos, ACIIW 2017 2018-Janua (2018 ), 147\u2013152. https:\/\/doi.org\/10.1109\/ACIIW.2017.8272605 arxiv:1708.05582 Sushant Hiray and Venkatesh Duppada. 2018. Agree to disagree: Improving disagreement detection with dual GRUs. 2017 7th International Conference on Affective Computing and Intelligent Interaction Workshops and Demos, ACIIW 2017 2018-Janua (2018), 147\u2013152. https:\/\/doi.org\/10.1109\/ACIIW.2017.8272605 arxiv:1708.05582"},{"key":"e_1_3_2_1_22_1","first-page":"2762","article-title":"AGREEMENT AND DISAGREEMENT CLASSIFICATION OF DYADIC INTERACTIONS USING VOCAL AND GESTURAL CUES Hossein Khaki, Elif Bozkurt, Engin Erzin Multimedia, Vision and Graphics Lab","volume":"2016","author":"Hossein Khaki Engin\u00a0Erzin","year":"2016","unstructured":"Engin\u00a0Erzin Hossein Khaki , Elif Bozkurt . 2016 . AGREEMENT AND DISAGREEMENT CLASSIFICATION OF DYADIC INTERACTIONS USING VOCAL AND GESTURAL CUES Hossein Khaki, Elif Bozkurt, Engin Erzin Multimedia, Vision and Graphics Lab , Koc. Icassp 2016 (2016), 2762 \u2013 2766 . Engin\u00a0Erzin Hossein Khaki, Elif Bozkurt. 2016. AGREEMENT AND DISAGREEMENT CLASSIFICATION OF DYADIC INTERACTIONS USING VOCAL AND GESTURAL CUES Hossein Khaki, Elif Bozkurt, Engin Erzin Multimedia, Vision and Graphics Lab, Koc. Icassp 2016 (2016), 2762\u20132766.","journal-title":"Koc. Icassp"},{"key":"e_1_3_2_1_23_1","doi-asserted-by":"crossref","unstructured":"Ahmet Iscen Giorgos Tolias Yannis Avrithis and Ondrej Chum. 2019. Label Propagation for Deep Semi-supervised Learning. arxiv:1904.04717\u00a0[cs.CV]  Ahmet Iscen Giorgos Tolias Yannis Avrithis and Ondrej Chum. 2019. Label Propagation for Deep Semi-supervised Learning. arxiv:1904.04717\u00a0[cs.CV]","DOI":"10.1109\/CVPR.2019.00521"},{"key":"e_1_3_2_1_24_1","volume-title":"Self-supervised Visual Feature Learning with Deep Neural Networks: A Survey. arXiv (feb","author":"Jing Longlong","year":"2019","unstructured":"Longlong Jing and Yingli Tian . 2019. Self-supervised Visual Feature Learning with Deep Neural Networks: A Survey. arXiv (feb 2019 ), 1\u201324. https:\/\/doi.org\/10.1109\/tpami.2020.2992393 arxiv:1902.06162 Longlong Jing and Yingli Tian. 2019. Self-supervised Visual Feature Learning with Deep Neural Networks: A Survey. arXiv (feb 2019), 1\u201324. https:\/\/doi.org\/10.1109\/tpami.2020.2992393 arxiv:1902.06162"},{"key":"e_1_3_2_1_25_1","doi-asserted-by":"crossref","unstructured":"Hwiyeol Jo and Ceyda Cinarel. 2019. Delta-training: Simple Semi-Supervised Text Classification using Pretrained Word Embeddings. EMNLP-IJCNLP 2019 - 2019 Conference on Empirical Methods in Natural Language Processing and 9th International Joint Conference on Natural Language Processing Proceedings of the Conference (jan 2019) 3458\u20133463. https:\/\/doi.org\/10.18653\/v1\/d19-1347 arxiv:1901.07651  Hwiyeol Jo and Ceyda Cinarel. 2019. Delta-training: Simple Semi-Supervised Text Classification using Pretrained Word Embeddings. EMNLP-IJCNLP 2019 - 2019 Conference on Empirical Methods in Natural Language Processing and 9th International Joint Conference on Natural Language Processing Proceedings of the Conference (jan 2019) 3458\u20133463. https:\/\/doi.org\/10.18653\/v1\/d19-1347 arxiv:1901.07651","DOI":"10.18653\/v1\/D19-1347"},{"key":"e_1_3_2_1_26_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2004.427"},{"key":"e_1_3_2_1_27_1","unstructured":"James Kunz. [n.d.]. Modern-Day Debate - YouTube. https:\/\/www.youtube.com\/c\/ModernDayDebate. (Accessed on 08\/20\/2020).  James Kunz. [n.d.]. Modern-Day Debate - YouTube. https:\/\/www.youtube.com\/c\/ModernDayDebate. (Accessed on 08\/20\/2020)."},{"key":"e_1_3_2_1_28_1","doi-asserted-by":"publisher","DOI":"10.1007\/s12369-012-0145-z"},{"key":"e_1_3_2_1_29_1","doi-asserted-by":"publisher","DOI":"10.1109\/FG.2011.5771418"},{"key":"e_1_3_2_1_30_1","volume-title":"ICML Workshop on Deep Learning for Audio, Speech and Language Processing 28(2013)","author":"Maas L","year":"2013","unstructured":"Andrew\u00a0 L Maas , Awni\u00a0 Y Hannun , and Andrew\u00a0 Y Ng . 2013 . Rectifier nonlinearities improve neural network acoustic models . in ICML Workshop on Deep Learning for Audio, Speech and Language Processing 28(2013) . Andrew\u00a0L Maas, Awni\u00a0Y Hannun, and Andrew\u00a0Y Ng. 2013. Rectifier nonlinearities improve neural network acoustic models. in ICML Workshop on Deep Learning for Audio, Speech and Language Processing 28(2013)."},{"key":"e_1_3_2_1_31_1","unstructured":"PBS NewsHour. [n.d.]. PBS NewsHour - Youtube. https:\/\/www.youtube.com\/playlist?list=PLgawtcOBBjr8o6ZfuuzSMpkz9E_a-LJRQ. (Accessed on 08\/20\/2020).  PBS NewsHour. [n.d.]. PBS NewsHour - Youtube. https:\/\/www.youtube.com\/playlist?list=PLgawtcOBBjr8o6ZfuuzSMpkz9E_a-LJRQ. (Accessed on 08\/20\/2020)."},{"key":"e_1_3_2_1_32_1","volume-title":"Proceedings of the 8th ACM International Conference on Bioinformatics, Computational Biology, and Health Informatics. 241\u2013246","author":"Ni Zhaoheng","year":"2017","unstructured":"Zhaoheng Ni , Ahmet\u00a0Cem Yuksel , Xiuyan Ni , Michael\u00a0 I Mandel , and Lei Xie . 2017 . Confused or not confused? Disentangling brain activity from EEG data using bidirectional LSTM recurrent neural networks . In Proceedings of the 8th ACM International Conference on Bioinformatics, Computational Biology, and Health Informatics. 241\u2013246 . Zhaoheng Ni, Ahmet\u00a0Cem Yuksel, Xiuyan Ni, Michael\u00a0I Mandel, and Lei Xie. 2017. Confused or not confused? Disentangling brain activity from EEG data using bidirectional LSTM recurrent neural networks. In Proceedings of the 8th ACM International Conference on Bioinformatics, Computational Biology, and Health Informatics. 241\u2013246."},{"key":"e_1_3_2_1_33_1","unstructured":"Graham Norton. [n.d.]. The Graham Norton Show - Youtube. https:\/\/www.youtube.com\/c\/OfficialGrahamNorton. (Accessed on 08\/20\/2020).  Graham Norton. [n.d.]. The Graham Norton Show - Youtube. https:\/\/www.youtube.com\/c\/OfficialGrahamNorton. (Accessed on 08\/20\/2020)."},{"key":"e_1_3_2_1_34_1","unstructured":"Yassine Ouali C\u00e9line Hudelot and Myriam Tami. 2020. An Overview of Deep Semi-Supervised Learning. (2020) 1\u201343. arxiv:2006.05278http:\/\/arxiv.org\/abs\/2006.05278  Yassine Ouali C\u00e9line Hudelot and Myriam Tami. 2020. An Overview of Deep Semi-Supervised Learning. (2020) 1\u201343. arxiv:2006.05278http:\/\/arxiv.org\/abs\/2006.05278"},{"key":"e_1_3_2_1_35_1","doi-asserted-by":"publisher","DOI":"10.1109\/JPROC.2003.817122"},{"key":"e_1_3_2_1_36_1","doi-asserted-by":"publisher","DOI":"10.1109\/TASLP.2020.3023632"},{"key":"e_1_3_2_1_37_1","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/W15-4625"},{"key":"e_1_3_2_1_38_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICCVW.2009.5457525"},{"key":"e_1_3_2_1_39_1","unstructured":"Kihyuk Sohn David Berthelot Chun\u00a0Liang Li Zizhao Zhang Nicholas Carlini Ekin\u00a0D. Cubuk Alex Kurakin Han Zhang and Colin Raffel. 2020. FixMatch: Simplifying semi-supervised learning with consistency and confidence. arXivNeurIPS(2020). arxiv:2001.07685  Kihyuk Sohn David Berthelot Chun\u00a0Liang Li Zizhao Zhang Nicholas Carlini Ekin\u00a0D. Cubuk Alex Kurakin Han Zhang and Colin Raffel. 2020. FixMatch: Simplifying semi-supervised learning with consistency and confidence. arXivNeurIPS(2020). arxiv:2001.07685"},{"key":"e_1_3_2_1_40_1","doi-asserted-by":"publisher","DOI":"10.5555\/1134782.1134792"},{"key":"e_1_3_2_1_41_1","volume-title":"Nips (nov","author":"van\u00a0den Oord Aaron","year":"2017","unstructured":"Aaron van\u00a0den Oord , Oriol Vinyals , and Koray Kavukcuoglu . 2017. Neural Discrete Representation Learning. Advances in Neural Information Processing Systems 2017-Decem , Nips (nov 2017 ), 6307\u20136316. arxiv:1711.00937http:\/\/arxiv.org\/abs\/1711.00937 Aaron van\u00a0den Oord, Oriol Vinyals, and Koray Kavukcuoglu. 2017. Neural Discrete Representation Learning. Advances in Neural Information Processing Systems 2017-Decem, Nips (nov 2017), 6307\u20136316. arxiv:1711.00937http:\/\/arxiv.org\/abs\/1711.00937"},{"key":"e_1_3_2_1_42_1","doi-asserted-by":"publisher","DOI":"10.1007\/s10994-019-05855-6"},{"key":"e_1_3_2_1_43_1","doi-asserted-by":"publisher","DOI":"10.1109\/TAFFC.2015.2507168"},{"key":"e_1_3_2_1_44_1","first-page":"374","article-title":"Detection of agreement and disagreement in broadcast conversations. ACL-HLT 2011 - Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics","volume":"2","author":"Wang Wen","year":"2011","unstructured":"Wen Wang , Sibel Yaman , Kristin Precoda , Colleen Richey , and Geoffrey Raymond . 2011 . Detection of agreement and disagreement in broadcast conversations. ACL-HLT 2011 - Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics : Human Language Technologies 2 (2011), 374 \u2013 378 . Wen Wang, Sibel Yaman, Kristin Precoda, Colleen Richey, and Geoffrey Raymond. 2011. Detection of agreement and disagreement in broadcast conversations. ACL-HLT 2011 - Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies 2 (2011), 374\u2013378.","journal-title":"Human Language Technologies"},{"key":"e_1_3_2_1_45_1","volume-title":"SeDMiD for Confusion Detection: Uncovering Mind State from Time Series Brain Wave Data. 1 (nov","author":"Yang Jingkang","year":"2016","unstructured":"Jingkang Yang , Haohan Wang , Jun Zhu , and Eric\u00a0 P. Xing . 2016. SeDMiD for Confusion Detection: Uncovering Mind State from Time Series Brain Wave Data. 1 (nov 2016 ), 1\u201311. arxiv:1611.10252http:\/\/arxiv.org\/abs\/1611.10252 Jingkang Yang, Haohan Wang, Jun Zhu, and Eric\u00a0P. Xing. 2016. SeDMiD for Confusion Detection: Uncovering Mind State from Time Series Brain Wave Data. 1 (nov 2016), 1\u201311. arxiv:1611.10252http:\/\/arxiv.org\/abs\/1611.10252"},{"key":"e_1_3_2_1_46_1","volume-title":"Wide Residual Networks. British Machine Vision Conference 2016, BMVC 2016 2016-September","author":"Zagoruyko Sergey","year":"2016","unstructured":"Sergey Zagoruyko and Nikos Komodakis . 2016 . Wide Residual Networks. British Machine Vision Conference 2016, BMVC 2016 2016-September (2016), 87.1\u201387.12. https:\/\/doi.org\/10.5244\/C.30.87 arxiv:1605.07146 Sergey Zagoruyko and Nikos Komodakis. 2016. Wide Residual Networks. British Machine Vision Conference 2016, BMVC 2016 2016-September (2016), 87.1\u201387.12. https:\/\/doi.org\/10.5244\/C.30.87 arxiv:1605.07146"},{"key":"e_1_3_2_1_47_1","volume-title":"Learner Affect through the Looking Glass: Characterization and Detection of Confusion in Online Courses","author":"Zeng Ziheng","year":"2017","unstructured":"Ziheng Zeng , Snigdha Chaturvedi , and Suma Bhat . 2017. Learner Affect through the Looking Glass: Characterization and Detection of Confusion in Online Courses . International Educational Data Mining Society ( 2017 ). Ziheng Zeng, Snigdha Chaturvedi, and Suma Bhat. 2017. Learner Affect through the Looking Glass: Characterization and Detection of Confusion in Online Courses.International Educational Data Mining Society (2017)."},{"key":"e_1_3_2_1_48_1","doi-asserted-by":"crossref","unstructured":"Xiaohua Zhai Avital Oliver Alexander Kolesnikov and Lucas Beyer. 2019. S4L: Self-Supervised Semi-Supervised Learning. arxiv:1905.03670\u00a0[cs.CV]  Xiaohua Zhai Avital Oliver Alexander Kolesnikov and Lucas Beyer. 2019. S4L: Self-Supervised Semi-Supervised Learning. arxiv:1905.03670\u00a0[cs.CV]","DOI":"10.1109\/ICCV.2019.00156"},{"key":"e_1_3_2_1_49_1","volume-title":"Confusion State Induction and EEG-based Detection in Learning. In 2018 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC). IEEE, 3290\u20133293","author":"Zhou Yun","year":"2018","unstructured":"Yun Zhou , Tao Xu , Shiqian Li , and Shaoqi Li . 2018 . Confusion State Induction and EEG-based Detection in Learning. In 2018 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC). IEEE, 3290\u20133293 . Yun Zhou, Tao Xu, Shiqian Li, and Shaoqi Li. 2018. Confusion State Induction and EEG-based Detection in Learning. In 2018 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC). IEEE, 3290\u20133293."},{"key":"e_1_3_2_1_50_1","volume-title":"Semi-Supervised Learning Literature Survey Contents. SciencesNew York 10, 1530","author":"Zhu Xiaojin","year":"2008","unstructured":"Xiaojin Zhu . 2008. Semi-Supervised Learning Literature Survey Contents. SciencesNew York 10, 1530 ( 2008 ), 10. https:\/\/doi.org\/10.1.1.146.2352 arxiv:1412.6596 Xiaojin Zhu. 2008. Semi-Supervised Learning Literature Survey Contents. SciencesNew York 10, 1530 (2008), 10. https:\/\/doi.org\/10.1.1.146.2352 arxiv:1412.6596"}],"event":{"name":"ICMI '21: INTERNATIONAL CONFERENCE ON MULTIMODAL INTERACTION","sponsor":["SIGCHI ACM Special Interest Group on Computer-Human Interaction"],"location":"Montreal QC Canada","acronym":"ICMI '21"},"container-title":["Companion Publication of the 2021 International Conference on Multimodal Interaction"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3461615.3486575","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3461615.3486575","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,17]],"date-time":"2025-06-17T20:49:04Z","timestamp":1750193344000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3461615.3486575"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,10,18]]},"references-count":50,"alternative-id":["10.1145\/3461615.3486575","10.1145\/3461615"],"URL":"https:\/\/doi.org\/10.1145\/3461615.3486575","relation":{},"subject":[],"published":{"date-parts":[[2021,10,18]]},"assertion":[{"value":"2021-12-17","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}