{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,25]],"date-time":"2026-01-25T03:04:19Z","timestamp":1769310259947,"version":"3.49.0"},"publisher-location":"New York, NY, USA","reference-count":51,"publisher":"ACM","license":[{"start":{"date-parts":[[2023,10,9]],"date-time":"2023-10-09T00:00:00Z","timestamp":1696809600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100013348","name":"Innosuisse - Schweizerische Agentur f\u00fcr Innovationsf\u00f6rderung","doi-asserted-by":"publisher","award":["29844.1"],"award-info":[{"award-number":["29844.1"]}],"id":[{"id":"10.13039\/501100013348","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Swiss National Science Foundation","award":["320038189096"],"award-info":[{"award-number":["320038189096"]}]}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2023,10,9]]},"DOI":"10.1145\/3577190.3614109","type":"proceedings-article","created":{"date-parts":[[2023,10,7]],"date-time":"2023-10-07T22:30:48Z","timestamp":1696717848000},"page":"84-93","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":2,"title":["Breathing New Life into COPD Assessment: Multisensory Home-monitoring for Predicting Severity"],"prefix":"10.1145","author":[{"ORCID":"https:\/\/orcid.org\/0009-0005-2107-2067","authenticated-orcid":false,"given":"Zixuan","family":"Xiao","sequence":"first","affiliation":[{"name":"ETH Zurich, Switzerland"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0763-2612","authenticated-orcid":false,"given":"Michal","family":"Muszynski","sequence":"additional","affiliation":[{"name":"IBM Research Europe, Switzerland"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8901-5062","authenticated-orcid":false,"given":"Ri\u010dards","family":"Marcinkevi\u010ds","sequence":"additional","affiliation":[{"name":"ETH Zurich, Switzerland"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1039-9572","authenticated-orcid":false,"given":"Lukas","family":"Zimmerli","sequence":"additional","affiliation":[{"name":"IBM Research Europe, Switzerland"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9140-0813","authenticated-orcid":false,"given":"Adam Daniel","family":"Ivankay","sequence":"additional","affiliation":[{"name":"IBM Research Europe, Switzerland"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6674-5193","authenticated-orcid":false,"given":"Dario","family":"Kohlbrenner","sequence":"additional","affiliation":[{"name":"University Hospital Zurich, Switzerland and University of Zurich, Switzerland"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1483-1318","authenticated-orcid":false,"given":"Manuel","family":"Kuhn","sequence":"additional","affiliation":[{"name":"University Hospital Zurich, Switzerland and University of Zurich, Switzerland"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9163-5663","authenticated-orcid":false,"given":"Yves","family":"Nordmann","sequence":"additional","affiliation":[{"name":"Docdok.health, Switzerland"}]},{"ORCID":"https:\/\/orcid.org\/0009-0002-3835-1650","authenticated-orcid":false,"given":"Ulrich","family":"Muehlner","sequence":"additional","affiliation":[{"name":"Docdok.health, Switzerland"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2158-2321","authenticated-orcid":false,"given":"Christian","family":"Clarenbach","sequence":"additional","affiliation":[{"name":"University Hospital Zurich, Switzerland"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6004-7770","authenticated-orcid":false,"given":"Julia E.","family":"Vogt","sequence":"additional","affiliation":[{"name":"ETH Zurich, Switzerland"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7254-3405","authenticated-orcid":false,"given":"Thomas","family":"Brunschwiler","sequence":"additional","affiliation":[{"name":"IBM Research Europe, Switzerland"}]}],"member":"320","published-online":{"date-parts":[[2023,10,9]]},"reference":[{"key":"e_1_3_2_1_1_1","doi-asserted-by":"publisher","DOI":"10.1183\/13993003.00239-2023"},{"key":"e_1_3_2_1_2_1","doi-asserted-by":"publisher","DOI":"10.2196\/18082"},{"key":"e_1_3_2_1_3_1","doi-asserted-by":"publisher","DOI":"10.1038\/nrdp.2015.76"},{"key":"e_1_3_2_1_4_1","doi-asserted-by":"publisher","DOI":"10.1109\/BIBE52308.2021.9635374"},{"key":"e_1_3_2_1_5_1","doi-asserted-by":"publisher","DOI":"10.1023\/A:1010933404324"},{"key":"e_1_3_2_1_6_1","doi-asserted-by":"publisher","DOI":"10.1613\/jair.953"},{"key":"e_1_3_2_1_8_1","doi-asserted-by":"publisher","DOI":"10.1145\/2939672.2939785"},{"key":"e_1_3_2_1_9_1","doi-asserted-by":"publisher","DOI":"10.1198\/jasa.2010.tm08281"},{"key":"e_1_3_2_1_10_1","first-page":"691","article-title":"Chronic Respiratory\u00a0Disease Collaborators. 2017. Global, regional, and national deaths, prevalence, disability-adjusted life years, and years lived with disability for chronic obstructive pulmonary disease and asthma, 1990\u20132015: A systematic analysis for the Global Burden of Disease Study 2015","volume":"5","author":"GBD","year":"2015","unstructured":"GBD 2015 Chronic Respiratory\u00a0Disease Collaborators. 2017. Global, regional, and national deaths, prevalence, disability-adjusted life years, and years lived with disability for chronic obstructive pulmonary disease and asthma, 1990\u20132015: A systematic analysis for the Global Burden of Disease Study 2015 . The Lancet Respiratory Medicine 5 , 9 (2017), 691 \u2013 706 . https:\/\/doi.org\/10.1016\/s2213-2600(17)30293-x 10.1016\/s2213-2600(17)30293-x GBD 2015 Chronic Respiratory\u00a0Disease Collaborators. 2017. Global, regional, and national deaths, prevalence, disability-adjusted life years, and years lived with disability for chronic obstructive pulmonary disease and asthma, 1990\u20132015: A systematic analysis for the Global Burden of Disease Study 2015. The Lancet Respiratory Medicine 5, 9 (2017), 691\u2013706. https:\/\/doi.org\/10.1016\/s2213-2600(17)30293-x","journal-title":"The Lancet Respiratory Medicine"},{"key":"e_1_3_2_1_11_1","doi-asserted-by":"publisher","DOI":"10.1002\/sam.11579"},{"key":"e_1_3_2_1_12_1","doi-asserted-by":"publisher","DOI":"10.7150\/ijms.58191"},{"key":"e_1_3_2_1_13_1","doi-asserted-by":"publisher","DOI":"10.5555\/3327757.3327923"},{"key":"e_1_3_2_1_14_1","doi-asserted-by":"crossref","unstructured":"Chang Gong Di Yao Chuzhe Zhang Wenbin Li and Jingping Bi. 2023. Causal Discovery from Temporal Data: An Overview and New Perspectives. arXiv:2303.10112  Chang Gong Di Yao Chuzhe Zhang Wenbin Li and Jingping Bi. 2023. Causal Discovery from Temporal Data: An Overview and New Perspectives. arXiv:2303.10112","DOI":"10.1145\/3580305.3599552"},{"key":"e_1_3_2_1_15_1","doi-asserted-by":"publisher","DOI":"10.2307\/1912791"},{"key":"e_1_3_2_1_16_1","volume-title":"A Telemonitoring and Hybrid Virtual Coaching Solution \"CAir\" for Patients with Chronic Obstructive Pulmonary Disease: Protocol for a Randomized Controlled Trial. JMIR research protocols 9, 10 (Oct","author":"Gross Christoph","year":"2020","unstructured":"Christoph Gross , Dario Kohlbrenner , Christian\u00a0 F. Clarenbach , Adam Ivankay , Thomas Brunschwiler , Yves Nordmann , and Florian V\u00a0Wangenheim . 2020. A Telemonitoring and Hybrid Virtual Coaching Solution \"CAir\" for Patients with Chronic Obstructive Pulmonary Disease: Protocol for a Randomized Controlled Trial. JMIR research protocols 9, 10 (Oct . 2020 ), e20412. https:\/\/doi.org\/10.2196\/20412 10.2196\/20412 Christoph Gross, Dario Kohlbrenner, Christian\u00a0F. Clarenbach, Adam Ivankay, Thomas Brunschwiler, Yves Nordmann, and Florian V\u00a0Wangenheim. 2020. A Telemonitoring and Hybrid Virtual Coaching Solution \"CAir\" for Patients with Chronic Obstructive Pulmonary Disease: Protocol for a Randomized Controlled Trial. JMIR research protocols 9, 10 (Oct. 2020), e20412. https:\/\/doi.org\/10.2196\/20412"},{"key":"e_1_3_2_1_17_1","volume-title":"Using a mobile health application to support self-management in chronic obstructive pulmonary disease: a six-month cohort study. BMC Medical Informatics and Decision Making 15, 1","author":"Hardinge Maxine","year":"2015","unstructured":"Maxine Hardinge , Heather Rutter , Carmelo Velardo , Syed\u00a0Ahmar Shah , Veronika Williams , Lionel Tarassenko , and Andrew Farmer . 2015. Using a mobile health application to support self-management in chronic obstructive pulmonary disease: a six-month cohort study. BMC Medical Informatics and Decision Making 15, 1 ( 2015 ). https:\/\/doi.org\/10.1186\/s12911-015-0171-5 10.1186\/s12911-015-0171-5 Maxine Hardinge, Heather Rutter, Carmelo Velardo, Syed\u00a0Ahmar Shah, Veronika Williams, Lionel Tarassenko, and Andrew Farmer. 2015. Using a mobile health application to support self-management in chronic obstructive pulmonary disease: a six-month cohort study. BMC Medical Informatics and Decision Making 15, 1 (2015). https:\/\/doi.org\/10.1186\/s12911-015-0171-5"},{"key":"e_1_3_2_1_18_1","volume-title":"2008 IEEE International Joint Conference on Neural Networks (IEEE World Congress on Computational Intelligence). IEEE","author":"He Haibo","year":"2008","unstructured":"Haibo He , Yang Bai , Edwardo\u00a0 A. Garcia , and Shutao Li . 2008 . ADASYN: Adaptive synthetic sampling approach for imbalanced learning . In 2008 IEEE International Joint Conference on Neural Networks (IEEE World Congress on Computational Intelligence). IEEE , Hong Kong, China, 1322\u20131328. https:\/\/doi.org\/10.1109\/IJCNN. 2008.4633969 10.1109\/IJCNN.2008.4633969 Haibo He, Yang Bai, Edwardo\u00a0A. Garcia, and Shutao Li. 2008. ADASYN: Adaptive synthetic sampling approach for imbalanced learning. In 2008 IEEE International Joint Conference on Neural Networks (IEEE World Congress on Computational Intelligence). IEEE, Hong Kong, China, 1322\u20131328. https:\/\/doi.org\/10.1109\/IJCNN.2008.4633969"},{"key":"e_1_3_2_1_19_1","doi-asserted-by":"publisher","DOI":"10.1162\/neco.1997.9.8.1735"},{"key":"e_1_3_2_1_20_1","first-page":"80","article-title":"Ridge Regression","volume":"42","author":"Hoerl E.","year":"2000","unstructured":"Arthur\u00a0 E. Hoerl and Robert\u00a0 W. Kennard . 2000 . Ridge Regression : Biased Estimation for Nonorthogonal Problems. Technometrics 42 , 1 (2000), 80 \u2013 86 . http:\/\/www.jstor.org\/stable\/1271436 Arthur\u00a0E. Hoerl and Robert\u00a0W. Kennard. 2000. Ridge Regression: Biased Estimation for Nonorthogonal Problems. Technometrics 42, 1 (2000), 80\u201386. http:\/\/www.jstor.org\/stable\/1271436","journal-title":"Biased Estimation for Nonorthogonal Problems. Technometrics"},{"key":"#cr-split#-e_1_3_2_1_21_1.1","doi-asserted-by":"crossref","unstructured":"\u00c5sa Holmner Fredrik \u00d6hberg Urban Wiklund Eva Bergmann Anders Blomberg and Karin Wadell. 2020. How stable is lung function in patients with stable chronic obstructive pulmonary disease when monitored using a telehealth system? A longitudinal and home-based study. BMC Medical Informatics and Decision Making 20 (2020). https:\/\/doi.org\/10.1186\/s12911-020-1103-6 10.1186\/s12911-020-1103-6","DOI":"10.1186\/s12911-020-1103-6"},{"key":"#cr-split#-e_1_3_2_1_21_1.2","doi-asserted-by":"crossref","unstructured":"\u00c5sa Holmner Fredrik \u00d6hberg Urban Wiklund Eva Bergmann Anders Blomberg and Karin Wadell. 2020. How stable is lung function in patients with stable chronic obstructive pulmonary disease when monitored using a telehealth system? A longitudinal and home-based study. BMC Medical Informatics and Decision Making 20 (2020). https:\/\/doi.org\/10.1186\/s12911-020-1103-6","DOI":"10.1186\/s12911-020-1103-6"},{"key":"e_1_3_2_1_22_1","article-title":"Digital interventions for the management of chronic obstructive pulmonary disease","volume":"2021","author":"Janjua Sadia","year":"2021","unstructured":"Sadia Janjua , Emma Banchoff , Christopher\u00a0 J.D. Threapleton , Samantha Prigmore , Joshua Fletcher , and Rebecca\u00a0 T. Disler . 2021 . Digital interventions for the management of chronic obstructive pulmonary disease . Cochrane Database of Systematic Reviews 2021 , 4 (2021). https:\/\/doi.org\/10.1002\/14651858.cd013246.pub2 10.1002\/14651858.cd013246.pub2 Sadia Janjua, Emma Banchoff, Christopher\u00a0J.D. Threapleton, Samantha Prigmore, Joshua Fletcher, and Rebecca\u00a0T. Disler. 2021. Digital interventions for the management of chronic obstructive pulmonary disease. Cochrane Database of Systematic Reviews 2021, 4 (2021). https:\/\/doi.org\/10.1002\/14651858.cd013246.pub2","journal-title":"Cochrane Database of Systematic Reviews"},{"key":"e_1_3_2_1_23_1","doi-asserted-by":"publisher","DOI":"10.1183\/09031936.00102509"},{"key":"e_1_3_2_1_24_1","volume-title":"Economy Statistical Recurrent Units For Inferring Nonlinear Granger Causality. In 8th International Conference on Learning Representations, ICLR 2020","author":"Khanna Saurabh","year":"2020","unstructured":"Saurabh Khanna and Vincent Y . \u00a0F. Tan. 2020 . Economy Statistical Recurrent Units For Inferring Nonlinear Granger Causality. In 8th International Conference on Learning Representations, ICLR 2020 , Addis Ababa, Ethiopia , April 26-30, 2020 . OpenReview.net, Addis Ababa, Ethiopia. https:\/\/openreview.net\/forum?id=SyxV9ANFDH Saurabh Khanna and Vincent Y.\u00a0F. Tan. 2020. Economy Statistical Recurrent Units For Inferring Nonlinear Granger Causality. In 8th International Conference on Learning Representations, ICLR 2020, Addis Ababa, Ethiopia, April 26-30, 2020. OpenReview.net, Addis Ababa, Ethiopia. https:\/\/openreview.net\/forum?id=SyxV9ANFDH"},{"key":"e_1_3_2_1_25_1","doi-asserted-by":"publisher","DOI":"10.2196\/31448"},{"key":"e_1_3_2_1_26_1","doi-asserted-by":"publisher","DOI":"10.1016\/S2213-2600(14)70001-3"},{"key":"#cr-split#-e_1_3_2_1_27_1.1","unstructured":"Qiuqiang Kong Yin Cao Turab Iqbal Yuxuan Wang Wenwu Wang and Mark Plumbley. 2019. PANNs: Large-Scale Pretrained Audio Neural Networks for Audio Pattern Recognition (Pretrained Models). https:\/\/doi.org\/10.5281\/zenodo.3987831 10.5281\/zenodo.3987831"},{"key":"#cr-split#-e_1_3_2_1_27_1.2","doi-asserted-by":"crossref","unstructured":"Qiuqiang Kong Yin Cao Turab Iqbal Yuxuan Wang Wenwu Wang and Mark Plumbley. 2019. PANNs: Large-Scale Pretrained Audio Neural Networks for Audio Pattern Recognition (Pretrained Models). https:\/\/doi.org\/10.5281\/zenodo.3987831","DOI":"10.1109\/TASLP.2020.3030497"},{"key":"e_1_3_2_1_28_1","doi-asserted-by":"publisher","DOI":"10.1016\/0304-4076(92)90104-Y"},{"key":"e_1_3_2_1_29_1","first-page":"1","article-title":"Imbalanced-learn: A Python Toolbox to Tackle the Curse of Imbalanced Datasets in Machine Learning","volume":"18","author":"Lema\u00eetre Guillaume","year":"2017","unstructured":"Guillaume Lema\u00eetre , Fernando Nogueira , and Christos\u00a0 K. Aridas . 2017 . Imbalanced-learn: A Python Toolbox to Tackle the Curse of Imbalanced Datasets in Machine Learning . Journal of Machine Learning Research 18 , 17 (2017), 1 \u2013 5 . http:\/\/jmlr.org\/papers\/v18\/16-365.html Guillaume Lema\u00eetre, Fernando Nogueira, and Christos\u00a0K. Aridas. 2017. Imbalanced-learn: A Python Toolbox to Tackle the Curse of Imbalanced Datasets in Machine Learning. Journal of Machine Learning Research 18, 17 (2017), 1\u20135. http:\/\/jmlr.org\/papers\/v18\/16-365.html","journal-title":"Journal of Machine Learning Research"},{"key":"e_1_3_2_1_30_1","first-page":"1","article-title":"LassoNet: A Neural Network with Feature Sparsity","volume":"22","author":"Lemhadri Ismael","year":"2021","unstructured":"Ismael Lemhadri , Feng Ruan , Louis Abraham , and Robert Tibshirani . 2021 . LassoNet: A Neural Network with Feature Sparsity . Journal of Machine Learning Research 22 , 127 (2021), 1 \u2013 29 . http:\/\/jmlr.org\/papers\/v22\/20-848.html Ismael Lemhadri, Feng Ruan, Louis Abraham, and Robert Tibshirani. 2021. LassoNet: A Neural Network with Feature Sparsity. Journal of Machine Learning Research 22, 127 (2021), 1\u201329. http:\/\/jmlr.org\/papers\/v22\/20-848.html","journal-title":"Journal of Machine Learning Research"},{"key":"e_1_3_2_1_31_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.jbi.2017.05.015"},{"key":"e_1_3_2_1_32_1","volume-title":"Interpretable Models for Granger Causality Using Self-explaining Neural Networks. In 9th International Conference on Learning Representations, ICLR 2021","author":"Marcinkevics Ricards","year":"2021","unstructured":"Ricards Marcinkevics and Julia\u00a0 E. Vogt . 2021 . Interpretable Models for Granger Causality Using Self-explaining Neural Networks. In 9th International Conference on Learning Representations, ICLR 2021 , Virtual Event, Austria , May 3-7, 2021. OpenReview.net, Virtual Event, Austria. https:\/\/openreview.net\/forum?id=DEa4JdMWRHp Ricards Marcinkevics and Julia\u00a0E. Vogt. 2021. Interpretable Models for Granger Causality Using Self-explaining Neural Networks. In 9th International Conference on Learning Representations, ICLR 2021, Virtual Event, Austria, May 3-7, 2021. OpenReview.net, Virtual Event, Austria. https:\/\/openreview.net\/forum?id=DEa4JdMWRHp"},{"key":"e_1_3_2_1_33_1","doi-asserted-by":"publisher","DOI":"10.1002\/widm.1493"},{"key":"e_1_3_2_1_34_1","doi-asserted-by":"publisher","DOI":"10.1111\/j.1467-9868.2007.00627.x"},{"key":"e_1_3_2_1_35_1","volume-title":"Deep Neural Network Based Cough Detection Using Bed-Mounted Accelerometer Measurements. In IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2021","author":"Pahar Madhurananda","year":"2021","unstructured":"Madhurananda Pahar , Igor D.\u00a0S. Miranda , Andreas\u00a0 H. Diacon , and Thomas Niesler . 2021 . Deep Neural Network Based Cough Detection Using Bed-Mounted Accelerometer Measurements. In IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2021 , Toronto, ON, Canada , June 6-11, 2021. IEEE, Toronto, ON, Canada, 8002\u20138006. https:\/\/doi.org\/10.1109\/ICASSP39728.2021.9414744 10.1109\/ICASSP39728.2021.9414744 Madhurananda Pahar, Igor D.\u00a0S. Miranda, Andreas\u00a0H. Diacon, and Thomas Niesler. 2021. Deep Neural Network Based Cough Detection Using Bed-Mounted Accelerometer Measurements. In IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2021, Toronto, ON, Canada, June 6-11, 2021. IEEE, Toronto, ON, Canada, 8002\u20138006. https:\/\/doi.org\/10.1109\/ICASSP39728.2021.9414744"},{"key":"e_1_3_2_1_36_1","doi-asserted-by":"publisher","DOI":"10.3390\/jpm12030379"},{"key":"e_1_3_2_1_37_1","doi-asserted-by":"publisher","DOI":"10.1038\/s41598-020-60042-1"},{"key":"e_1_3_2_1_38_1","doi-asserted-by":"publisher","DOI":"10.3390\/life12040499"},{"key":"e_1_3_2_1_39_1","volume-title":"The Six-Minute Stepper Test Is Valid to Evaluate Functional Capacity in Hospitalized Patients With Exacerbated COPD. Frontiers in Physiology 13","author":"Ribeiro Diego\u00a0Britto","year":"2022","unstructured":"Diego\u00a0Britto Ribeiro , Aline\u00a0Carleto Terrazas , and Wellington\u00a0Pereira Yamaguti . 2022. The Six-Minute Stepper Test Is Valid to Evaluate Functional Capacity in Hospitalized Patients With Exacerbated COPD. Frontiers in Physiology 13 ( 2022 ). https:\/\/doi.org\/10.3389\/fphys.2022.853434 10.3389\/fphys.2022.853434 Diego\u00a0Britto Ribeiro, Aline\u00a0Carleto Terrazas, and Wellington\u00a0Pereira Yamaguti. 2022. The Six-Minute Stepper Test Is Valid to Evaluate Functional Capacity in Hospitalized Patients With Exacerbated COPD. Frontiers in Physiology 13 (2022). https:\/\/doi.org\/10.3389\/fphys.2022.853434"},{"key":"e_1_3_2_1_40_1","doi-asserted-by":"publisher","DOI":"10.1111\/ecog.02881"},{"key":"e_1_3_2_1_41_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2017.02.029"},{"key":"e_1_3_2_1_42_1","volume-title":"Biomarkers in chronic obstructive pulmonary disease: confusing or useful?International Journal of Chronic Obstructive Pulmonary Disease 9, 1","author":"Stockley A.","year":"2014","unstructured":"Robert\u00a0 A. Stockley . 2014. Biomarkers in chronic obstructive pulmonary disease: confusing or useful?International Journal of Chronic Obstructive Pulmonary Disease 9, 1 ( 2014 ), 163\u2013177. Robert\u00a0A. Stockley. 2014. Biomarkers in chronic obstructive pulmonary disease: confusing or useful?International Journal of Chronic Obstructive Pulmonary Disease 9, 1 (2014), 163\u2013177."},{"key":"e_1_3_2_1_43_1","first-page":"4267","article-title":"Neural Granger Causality","volume":"44","author":"Tank Alex","year":"2021","unstructured":"Alex Tank , Ian Covert , Nicholas Foti , Ali Shojaie , and Emily\u00a0 B. Fox . 2021 . Neural Granger Causality . IEEE Transactions on Pattern Analysis and Machine Intelligence 44 , 08 (2021), 4267 \u2013 4279 . https:\/\/doi.org\/10.1109\/tpami.2021.3065601 10.1109\/tpami.2021.3065601 Alex Tank, Ian Covert, Nicholas Foti, Ali Shojaie, and Emily\u00a0B. Fox. 2021. Neural Granger Causality. IEEE Transactions on Pattern Analysis and Machine Intelligence 44, 08 (2021), 4267\u20134279. https:\/\/doi.org\/10.1109\/tpami.2021.3065601","journal-title":"IEEE Transactions on Pattern Analysis and Machine Intelligence"},{"key":"e_1_3_2_1_44_1","doi-asserted-by":"publisher","DOI":"10.1111\/j.2517-6161.1996.tb02080.x"},{"key":"e_1_3_2_1_45_1","first-page":"1","article-title":"mice: Multivariate Imputation by Chained Equations in R","volume":"45","author":"van Buuren Stef","year":"2011","unstructured":"Stef van Buuren and Karin Groothuis-Oudshoorn . 2011 . mice: Multivariate Imputation by Chained Equations in R . Journal of Statistical Software 45 , 3 (2011), 1 \u2013 67 . https:\/\/doi.org\/10.18637\/jss.v045.i03 10.18637\/jss.v045.i03 Stef van Buuren and Karin Groothuis-Oudshoorn. 2011. mice: Multivariate Imputation by Chained Equations in R. Journal of Statistical Software 45, 3 (2011), 1\u201367. https:\/\/doi.org\/10.18637\/jss.v045.i03","journal-title":"Journal of Statistical Software"},{"key":"e_1_3_2_1_46_1","volume-title":"Willmott and Kenji Matsuura","author":"J.","year":"2005","unstructured":"Cort\u00a0 J. Willmott and Kenji Matsuura . 2005 . Advantages of the mean absolute error (MAE) over the root mean square error (RMSE) in assessing average model performance. Climate research 30, 1 (2005), 79\u201382. https:\/\/www.jstor.org\/stable\/24869236 Cort\u00a0J. Willmott and Kenji Matsuura. 2005. Advantages of the mean absolute error (MAE) over the root mean square error (RMSE) in assessing average model performance. Climate research 30, 1 (2005), 79\u201382. https:\/\/www.jstor.org\/stable\/24869236"},{"key":"e_1_3_2_1_47_1","volume-title":"Machine Learning, and Deep Learning: Development and Cohort Study. JMIR mHealth and uHealth 9, 5","author":"Wu Chia-Tung","year":"2021","unstructured":"Chia-Tung Wu , Guo-Hung Li , Chun-Ta Huang , Yu-Chieh Cheng , Chi-Hsien Chen , Jung-Yien Chien , Ping-Hung Kuo , Lu-Cheng Kuo , and Feipei Lai . 2021. Acute Exacerbation of a Chronic Obstructive Pulmonary Disease Prediction System Using Wearable Device Data , Machine Learning, and Deep Learning: Development and Cohort Study. JMIR mHealth and uHealth 9, 5 ( 2021 ), e22591. https:\/\/doi.org\/10.2196\/22591 10.2196\/22591 Chia-Tung Wu, Guo-Hung Li, Chun-Ta Huang, Yu-Chieh Cheng, Chi-Hsien Chen, Jung-Yien Chien, Ping-Hung Kuo, Lu-Cheng Kuo, and Feipei Lai. 2021. Acute Exacerbation of a Chronic Obstructive Pulmonary Disease Prediction System Using Wearable Device Data, Machine Learning, and Deep Learning: Development and Cohort Study. JMIR mHealth and uHealth 9, 5 (2021), e22591. https:\/\/doi.org\/10.2196\/22591"},{"key":"e_1_3_2_1_48_1","first-page":"531","article-title":"Hierarchical Sparse Modeling","volume":"32","author":"Yan Xiaohan","year":"2017","unstructured":"Xiaohan Yan and Jacob Bien . 2017 . Hierarchical Sparse Modeling : A Choice of Two Group Lasso Formulations. Statist. Sci. 32 , 4 (2017), 531 \u2013 560 . https:\/\/doi.org\/10.1214\/17-sts622 10.1214\/17-sts622 Xiaohan Yan and Jacob Bien. 2017. Hierarchical Sparse Modeling: A Choice of Two Group Lasso Formulations. Statist. Sci. 32, 4 (2017), 531\u2013560. https:\/\/doi.org\/10.1214\/17-sts622","journal-title":"A Choice of Two Group Lasso Formulations. Statist. Sci."},{"key":"e_1_3_2_1_49_1","volume-title":"Proceedings of the 38th International Conference on Machine Learning(Proceedings of Machine Learning Research, Vol.\u00a0139)","author":"Yang Yuzhe","year":"2021","unstructured":"Yuzhe Yang , Kaiwen Zha , Yingcong Chen , Hao Wang , and Dina Katabi . 2021 . Delving into Deep Imbalanced Regression . In Proceedings of the 38th International Conference on Machine Learning(Proceedings of Machine Learning Research, Vol.\u00a0139) , Marina Meila and Tong Zhang (Eds.). PMLR, Virtual, 1 1842\u201311851. https:\/\/proceedings.mlr.press\/v139\/yang21m.html Yuzhe Yang, Kaiwen Zha, Yingcong Chen, Hao Wang, and Dina Katabi. 2021. Delving into Deep Imbalanced Regression. In Proceedings of the 38th International Conference on Machine Learning(Proceedings of Machine Learning Research, Vol.\u00a0139), Marina Meila and Tong Zhang (Eds.). PMLR, Virtual, 11842\u201311851. https:\/\/proceedings.mlr.press\/v139\/yang21m.html"},{"key":"e_1_3_2_1_50_1","doi-asserted-by":"publisher","DOI":"10.1111\/j.1467-9868.2005.00532.x"}],"event":{"name":"ICMI '23: INTERNATIONAL CONFERENCE ON MULTIMODAL INTERACTION","location":"Paris France","acronym":"ICMI '23","sponsor":["SIGCHI ACM Special Interest Group on Computer-Human Interaction"]},"container-title":["INTERNATIONAL CONFERENCE ON MULTIMODAL INTERACTION"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3577190.3614109","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3577190.3614109","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,17]],"date-time":"2025-06-17T17:51:11Z","timestamp":1750182671000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3577190.3614109"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,10,9]]},"references-count":51,"alternative-id":["10.1145\/3577190.3614109","10.1145\/3577190"],"URL":"https:\/\/doi.org\/10.1145\/3577190.3614109","relation":{},"subject":[],"published":{"date-parts":[[2023,10,9]]},"assertion":[{"value":"2023-10-09","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}