{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,3]],"date-time":"2026-07-03T15:23:34Z","timestamp":1783092214278,"version":"3.54.6"},"publisher-location":"New York, NY, USA","reference-count":39,"publisher":"ACM","license":[{"start":{"date-parts":[[2024,3,4]],"date-time":"2024-03-04T00:00:00Z","timestamp":1709510400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2024,3,4]]},"DOI":"10.1145\/3616855.3635795","type":"proceedings-article","created":{"date-parts":[[2024,3,4]],"date-time":"2024-03-04T18:18:12Z","timestamp":1709576292000},"page":"152-160","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":21,"title":["CroSSL: Cross-modal Self-Supervised Learning for Time-series through Latent Masking"],"prefix":"10.1145","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-8150-120X","authenticated-orcid":false,"given":"Shohreh","family":"Deldari","sequence":"first","affiliation":[{"name":"University of New South Wales, Sydney, Australia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9761-951X","authenticated-orcid":false,"given":"Dimitris","family":"Spathis","sequence":"additional","affiliation":[{"name":"Nokia Bell Labs, Cambridge, United Kingdom"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4247-906X","authenticated-orcid":false,"given":"Mohammad","family":"Malekzadeh","sequence":"additional","affiliation":[{"name":"Nokia Bell Labs, Cambridge, United Kingdom"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5057-9557","authenticated-orcid":false,"given":"Fahim","family":"Kawsar","sequence":"additional","affiliation":[{"name":"Nokia Bell Labs, Cambridge, United Kingdom"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1237-1664","authenticated-orcid":false,"given":"Flora D.","family":"Salim","sequence":"additional","affiliation":[{"name":"University of New South Wales, Sydney, Australia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1475-3017","authenticated-orcid":false,"given":"Akhil","family":"Mathur","sequence":"additional","affiliation":[{"name":"Nokia Bell Labs, Cambridge, United Kingdom"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"320","published-online":{"date-parts":[[2024,3,4]]},"reference":[{"key":"e_1_3_2_1_1_1","volume-title":"MultiMAE: Multi-modal Multi-task Masked Autoencoders. arXiv preprint arXiv:2204.01678","author":"Bachmann Roman","year":"2022","unstructured":"Roman Bachmann, David Mizrahi, Andrei Atanov, and Amir Zamir. 2022. MultiMAE: Multi-modal Multi-task Masked Autoencoders. arXiv preprint arXiv:2204.01678 (2022)."},{"key":"e_1_3_2_1_2_1","volume-title":"wav2vec 2.0: A framework for self-supervised learning of speech representations. Advances in neural information processing systems","author":"Baevski Alexei","year":"2020","unstructured":"Alexei Baevski, Yuhao Zhou, Abdelrahman Mohamed, and Michael Auli. 2020. wav2vec 2.0: A framework for self-supervised learning of speech representations. Advances in neural information processing systems , Vol. 33 (2020), 12449--12460."},{"key":"e_1_3_2_1_3_1","volume-title":"VICReg: Variance-Invariance-Covariance Regularization for Self-Supervised Learning. In International Conference on Learning Representations. https:\/\/openreview.net\/forum?id=xm6YD62D1Ub","author":"Bardes Adrien","year":"2022","unstructured":"Adrien Bardes, Jean Ponce, and Yann LeCun. 2022. VICReg: Variance-Invariance-Covariance Regularization for Self-Supervised Learning. In International Conference on Learning Representations. https:\/\/openreview.net\/forum?id=xm6YD62D1Ub"},{"key":"e_1_3_2_1_4_1","volume-title":"International conference on machine learning. PMLR, 1597--1607","author":"Chen Ting","year":"2020","unstructured":"Ting Chen, Simon Kornblith, Mohammad Norouzi, and Geoffrey Hinton. 2020. A simple framework for contrastive learning of visual representations. In International conference on machine learning. PMLR, 1597--1607."},{"key":"e_1_3_2_1_5_1","volume-title":"Lin (Eds.)","volume":"33","author":"Chuang Ching-Yao","year":"2020","unstructured":"Ching-Yao Chuang, Joshua Robinson, Yen-Chen Lin, Antonio Torralba, and Stefanie Jegelka. 2020. Debiased Contrastive Learning. In Advances in Neural Information Processing Systems, H. Larochelle, M. Ranzato, R. Hadsell, M. F. Balcan, and H. Lin (Eds.), Vol. 33. Curran Associates, Inc. https:\/\/proceedings.neurips.cc\/paper\/2020\/file\/63c3ddcc7b23daa1e42dc41f9a44a873-Paper.pdf"},{"key":"e_1_3_2_1_6_1","doi-asserted-by":"publisher","DOI":"10.1145\/3442381.3449903"},{"key":"e_1_3_2_1_7_1","volume-title":"COCOA: Cross Modality Contrastive Learning for Sensor Data. arXiv preprint arXiv:2208.00467","author":"Deldari Shohreh","year":"2022","unstructured":"Shohreh Deldari, Hao Xue, Aaqib Saeed, Daniel V Smith, and Flora D Salim. 2022. COCOA: Cross Modality Contrastive Learning for Sensor Data. arXiv preprint arXiv:2208.00467 (2022)."},{"key":"e_1_3_2_1_8_1","volume-title":"International Conference on Learning Representations (ICLR).","author":"Federici Marco","year":"2020","unstructured":"Marco Federici, Anjan Dutta, Patrick Forr\u00e9, Nate Kushman, and Zeynep Akata. 2020. Learning robust representations via multi-view information bottleneck. International Conference on Learning Representations (ICLR)."},{"key":"e_1_3_2_1_9_1","volume-title":"Leon Glass, Jeffrey M Hausdorff, Plamen Ch Ivanov, Roger G Mark, Joseph E Mietus, George B Moody, Chung-Kang Peng, and H Eugene Stanley.","author":"Goldberger Ary L","year":"2000","unstructured":"Ary L Goldberger, Luis AN Amaral, Leon Glass, Jeffrey M Hausdorff, Plamen Ch Ivanov, Roger G Mark, Joseph E Mietus, George B Moody, Chung-Kang Peng, and H Eugene Stanley. 2000. PhysioBank, PhysioToolkit, and PhysioNet: components of a new research resource for complex physiologic signals. Circulation , Vol. 101, 23 (2000)."},{"key":"e_1_3_2_1_10_1","volume-title":"Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020","author":"Grill Jean-Bastien","year":"2020","unstructured":"Jean-Bastien Grill, Florian Strub, Florent Altch\u00e9 , Corentin Tallec, Pierre H. Richemond, Elena Buchatskaya, Carl Doersch, Bernardo \u00c1 vila Pires, Zhaohan Guo, Mohammad Gheshlaghi Azar, Bilal Piot, Koray Kavukcuoglu, R\u00e9 mi Munos, and Michal Valko. 2020. Bootstrap Your Own Latent - A New Approach to Self-Supervised Learning. In Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, NeurIPS 2020, December 6--12, 2020, virtual."},{"key":"e_1_3_2_1_11_1","doi-asserted-by":"publisher","DOI":"10.1145\/3410531.3414306"},{"key":"e_1_3_2_1_12_1","doi-asserted-by":"publisher","DOI":"10.1145\/3463506"},{"key":"e_1_3_2_1_13_1","doi-asserted-by":"publisher","DOI":"10.1145\/3550299"},{"key":"e_1_3_2_1_14_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52688.2022.01553"},{"key":"e_1_3_2_1_15_1","volume-title":"International Conference on Machine Learning (ICML). PMLR.","author":"Henaff Olivier J","unstructured":"Olivier J Henaff, Aravind Srinivas, Jeffrey De Fauw, Ali Razavi, Carl Doersch, S. M. Ali Eslami, and Aaron van den Oord. 2020. Data-efficient image recognition with contrastive predictive coding. In International Conference on Machine Learning (ICML). PMLR."},{"key":"e_1_3_2_1_16_1","doi-asserted-by":"publisher","DOI":"10.1145\/3410531.3414311"},{"key":"e_1_3_2_1_17_1","doi-asserted-by":"publisher","DOI":"10.1145\/3517246"},{"key":"e_1_3_2_1_18_1","doi-asserted-by":"publisher","DOI":"10.1109\/10.867928"},{"key":"e_1_3_2_1_19_1","doi-asserted-by":"publisher","DOI":"10.1109\/TASLP.2021.3095662"},{"key":"e_1_3_2_1_20_1","doi-asserted-by":"publisher","DOI":"10.3390\/bios12020073"},{"key":"e_1_3_2_1_21_1","volume-title":"Representation learning with contrastive predictive coding. arXiv preprint arXiv:1807.03748","author":"van den Oord Aaron","year":"2018","unstructured":"Aaron van den Oord, Yazhe Li, and Oriol Vinyals. 2018. Representation learning with contrastive predictive coding. arXiv preprint arXiv:1807.03748 (2018)."},{"key":"e_1_3_2_1_22_1","doi-asserted-by":"publisher","DOI":"10.3390\/s16010115"},{"key":"e_1_3_2_1_23_1","doi-asserted-by":"publisher","DOI":"10.1145\/3459666"},{"key":"e_1_3_2_1_24_1","doi-asserted-by":"publisher","DOI":"10.1145\/3161174"},{"key":"e_1_3_2_1_25_1","doi-asserted-by":"publisher","DOI":"10.1109\/ISWC.2012.13"},{"key":"e_1_3_2_1_26_1","volume-title":"Contrastive Learning with Hard Negative Samples. In International Conference on Learning Representations. https:\/\/openreview.net\/forum?id=CR1XOQ0UTh-","author":"Robinson Joshua David","year":"2021","unstructured":"Joshua David Robinson, Ching-Yao Chuang, Suvrit Sra, and Stefanie Jegelka. 2021. Contrastive Learning with Hard Negative Samples. In International Conference on Learning Representations. https:\/\/openreview.net\/forum?id=CR1XOQ0UTh-"},{"key":"e_1_3_2_1_27_1","doi-asserted-by":"publisher","DOI":"10.1145\/3328932"},{"key":"e_1_3_2_1_28_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.mlwa.2021.100152"},{"key":"e_1_3_2_1_29_1","volume-title":"On the Information Bottleneck Theory of Deep Learning. In International Conference on Learning Representations. https:\/\/openreview.net\/forum?id=ry_WPG-A-","author":"Saxe Andrew Michael","year":"2018","unstructured":"Andrew Michael Saxe, Yamini Bansal, Joel Dapello, Madhu Advani, Artemy Kolchinsky, Brendan Daniel Tracey, and David Daniel Cox. 2018. On the Information Bottleneck Theory of Deep Learning. In International Conference on Learning Representations. https:\/\/openreview.net\/forum?id=ry_WPG-A-"},{"key":"e_1_3_2_1_30_1","doi-asserted-by":"publisher","DOI":"10.1145\/3242969.3242985"},{"key":"e_1_3_2_1_31_1","volume-title":"To Compress or Not to Compress--Self-Supervised Learning and Information Theory: A Review. arXiv preprint arXiv:2304.09355","author":"Shwartz-Ziv Ravid","year":"2023","unstructured":"Ravid Shwartz-Ziv and Yann LeCun. 2023. To Compress or Not to Compress--Self-Supervised Learning and Information Theory: A Review. arXiv preprint arXiv:2304.09355 (2023)."},{"key":"e_1_3_2_1_32_1","doi-asserted-by":"publisher","DOI":"10.1145\/3450439.3451863"},{"key":"e_1_3_2_1_33_1","volume-title":"Selfhar: Improving human activity recognition through self-training with unlabeled data. arXiv preprint arXiv:2102.06073","author":"Tang Chi Ian","year":"2021","unstructured":"Chi Ian Tang, Ignacio Perez-Pozuelo, Dimitris Spathis, Soren Brage, Nick Wareham, and Cecilia Mascolo. 2021. Selfhar: Improving human activity recognition through self-training with unlabeled data. arXiv preprint arXiv:2102.06073 (2021)."},{"key":"e_1_3_2_1_34_1","volume-title":"Contrastive multiview coding. arXiv preprint arXiv:1906.05849","author":"Tian Yonglong","year":"2019","unstructured":"Yonglong Tian, Dilip Krishnan, and Phillip Isola. 2019. Contrastive multiview coding. arXiv preprint arXiv:1906.05849 (2019)."},{"key":"e_1_3_2_1_35_1","volume-title":"Unsupervised representation learning for time series with temporal neighborhood coding. arXiv preprint arXiv:2106.00750","author":"Tonekaboni Sana","year":"2021","unstructured":"Sana Tonekaboni, Danny Eytan, and Anna Goldenberg. 2021. Unsupervised representation learning for time series with temporal neighborhood coding. arXiv preprint arXiv:2106.00750 (2021)."},{"key":"e_1_3_2_1_36_1","doi-asserted-by":"publisher","DOI":"10.1145\/3447548.3467263"},{"key":"e_1_3_2_1_37_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2021.03.090"},{"key":"e_1_3_2_1_38_1","volume-title":"Self-supervised Learning for Human Activity Recognition Using 700,000 Person-days of Wearable Data. arXiv preprint arXiv:2206.02909","author":"Yuan Hang","year":"2022","unstructured":"Hang Yuan, Shing Chan, Andrew P Creagh, Catherine Tong, David A Clifton, and Aiden Doherty. 2022. Self-supervised Learning for Human Activity Recognition Using 700,000 Person-days of Wearable Data. arXiv preprint arXiv:2206.02909 (2022)."},{"key":"e_1_3_2_1_39_1","volume-title":"Proceedings of the 38th International Conference on Machine Learning, ICML, , Marina Meila and Tong Zhang (Eds.)","volume":"139","author":"Zbontar Jure","year":"2021","unstructured":"Jure Zbontar, Li Jing, Ishan Misra, Yann LeCun, and St\u00e9 phane Deny. 2021. Barlow Twins: Self-Supervised Learning via Redundancy Reduction. In Proceedings of the 38th International Conference on Machine Learning, ICML, , Marina Meila and Tong Zhang (Eds.), Vol. 139. PMLR. io"}],"event":{"name":"WSDM '24: The 17th ACM International Conference on Web Search and Data Mining","location":"Merida Mexico","acronym":"WSDM '24","sponsor":["SIGMOD ACM Special Interest Group on Management of Data","SIGWEB ACM Special Interest Group on Hypertext, Hypermedia, and Web","SIGKDD ACM Special Interest Group on Knowledge Discovery in Data","SIGIR ACM Special Interest Group on Information Retrieval"]},"container-title":["Proceedings of the 17th ACM International Conference on Web Search and Data Mining"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3616855.3635795","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3616855.3635795","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,8,22]],"date-time":"2025-08-22T00:47:14Z","timestamp":1755823634000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3616855.3635795"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,3,4]]},"references-count":39,"alternative-id":["10.1145\/3616855.3635795","10.1145\/3616855"],"URL":"https:\/\/doi.org\/10.1145\/3616855.3635795","relation":{},"subject":[],"published":{"date-parts":[[2024,3,4]]},"assertion":[{"value":"2024-03-04","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}