{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,6]],"date-time":"2026-06-06T07:02:19Z","timestamp":1780729339480,"version":"3.54.1"},"publisher-location":"Singapore","reference-count":28,"publisher":"Springer Nature Singapore","isbn-type":[{"value":"9789819214617","type":"print"},{"value":"9789819214624","type":"electronic"}],"license":[{"start":{"date-parts":[[2026,1,1]],"date-time":"2026-01-01T00:00:00Z","timestamp":1767225600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2026,1,1]],"date-time":"2026-01-01T00:00:00Z","timestamp":1767225600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2026]]},"DOI":"10.1007\/978-981-92-1462-4_27","type":"book-chapter","created":{"date-parts":[[2026,6,6]],"date-time":"2026-06-06T06:47:00Z","timestamp":1780728420000},"page":"341-353","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["TS-Unlearn: A Dual-Objective Unlearning Framework for\u00a0Time Series Forecasting"],"prefix":"10.1007","author":[{"given":"Ziyi","family":"Wang","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Lixing","family":"Chen","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zhongqi","family":"Miao","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Junhua","family":"Tang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yang","family":"Bai","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jianhua","family":"Li","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2026,6,7]]},"reference":[{"key":"27_CR1","unstructured":"Bubeck, S.: Sparks of artificial general intelligence: Early experiments with GPT-4 (2023). arXiv:2303.12712"},{"key":"27_CR2","doi-asserted-by":"crossref","unstructured":"Lukas, N., et al.: Analyzing leakage of personally identifiable information in language models. In: 2023 IEEE Symposium on Security and Privacy (SP), pp. 346\u2013363. IEEE (2023)","DOI":"10.1109\/SP46215.2023.10179300"},{"issue":"5","key":"27_CR3","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1145\/3749987","volume":"16","author":"TT Nguyen","year":"2025","unstructured":"Nguyen, T.T., et al.: A survey of machine unlearning. ACM Trans. Intell. Syst. Technol. 16(5), 1\u201346 (2025)","journal-title":"ACM Trans. Intell. Syst. Technol."},{"key":"27_CR4","first-page":"8780","volume":"34","author":"P Dhariwal","year":"2021","unstructured":"Dhariwal, P., Nichol, A.: Diffusion models beat GANS on image synthesis. Adv. Neural. Inf. Process. Syst. 34, 8780\u20138794 (2021)","journal-title":"Adv. Neural. Inf. Process. Syst."},{"issue":"9","key":"27_CR5","doi-asserted-by":"publisher","first-page":"13046","DOI":"10.1109\/TNNLS.2023.3266233","volume":"35","author":"AK Tarun","year":"2023","unstructured":"Tarun, A.K., et al.: Fast yet effective machine unlearning. IEEE Trans. Neural Netw. Learn. Syst. 35(9), 13046\u201313055 (2023)","journal-title":"IEEE Trans. Neural Netw. Learn. Syst."},{"issue":"2194","key":"27_CR6","doi-asserted-by":"publisher","first-page":"20200209","DOI":"10.1098\/rsta.2020.0209","volume":"379","author":"B Lim","year":"2021","unstructured":"Lim, B., Zohren, S.: Time-series forecasting with deep learning: a survey. Phil. Trans. R. Soc. A 379(2194), 20200209 (2021)","journal-title":"Phil. Trans. R. Soc. A"},{"issue":"4","key":"27_CR7","first-page":"1544","volume":"34","author":"DA Tedjopurnomo","year":"2020","unstructured":"Tedjopurnomo, D.A., Bao, Z., Zheng, B., Choudhury, F.M., Qin, A.K.: A survey on modern deep neural network for traffic prediction: trends, methods and challenges. IEEE Trans. Knowl. Data Eng. 34(4), 1544\u20131561 (2020)","journal-title":"IEEE Trans. Knowl. Data Eng."},{"key":"27_CR8","doi-asserted-by":"publisher","first-page":"902","DOI":"10.1016\/j.rser.2017.02.085","volume":"74","author":"C Deb","year":"2017","unstructured":"Deb, C., Zhang, F., Yang, J., Lee, S.E., Shah, K.W.: A review on time series forecasting techniques for building energy consumption. Renew. Sustain. Energy Rev. 74, 902\u2013924 (2017)","journal-title":"Renew. Sustain. Energy Rev."},{"key":"27_CR9","doi-asserted-by":"publisher","first-page":"310","DOI":"10.1016\/j.earscirev.2018.12.005","volume":"190","author":"M Mudelsee","year":"2019","unstructured":"Mudelsee, M.: Trend analysis of climate time series: a review of methods. Earth Sci. Rev. 190, 310\u2013322 (2019)","journal-title":"Earth Sci. Rev."},{"key":"27_CR10","doi-asserted-by":"crossref","unstructured":"Bourtoule, L.: Machine unlearning. 2021 IEEE symposium on security and privacy (SP), pp. 141\u2013159. IEEE (2021)","DOI":"10.1109\/SP40001.2021.00019"},{"key":"27_CR11","doi-asserted-by":"crossref","unstructured":"Golatkar, A., Achille, A., Soatto, S.: Eternal sunshine of the spotless net: selective forgetting in deep networks. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 9304\u20139312 (2020)","DOI":"10.1109\/CVPR42600.2020.00932"},{"key":"27_CR12","doi-asserted-by":"crossref","unstructured":"Graves, L., Nagisetty, V., Ganesh, V.: Amnesiac machine learning. In: Proceedings of the AAAI Conference on Artificial Intelligence, vol. 35, pp. 11516\u201311524 (2021)","DOI":"10.1609\/aaai.v35i13.17371"},{"key":"27_CR13","unstructured":"Tarun, A.K.: Deep regression unlearning. In: International Conference on Machine Learning, pp. 33921\u201333939. PMLR (2023)"},{"key":"27_CR14","first-page":"1957","volume":"36","author":"M Kurmanji","year":"2023","unstructured":"Kurmanji, M., et al.: Towards unbounded machine unlearning. Adv. Neural. Inf. Process. Syst. 36, 1957\u20131987 (2023)","journal-title":"Adv. Neural. Inf. Process. Syst."},{"key":"27_CR15","unstructured":"Li, G., Hsu, H., Chen, C.F., Marculescu, R.: Machine unlearning for image-to-image generative models (2024). arXiv:2402.00351"},{"key":"27_CR16","doi-asserted-by":"crossref","unstructured":"Zhou, H.: Informer: Beyond efficient transformer for long sequence time-series forecasting. In: Proceedings of the AAAI Conference on Artificial Intelligence, vol. 35, pp. 11106\u201311115 (2021)","DOI":"10.1609\/aaai.v35i12.17325"},{"key":"27_CR17","first-page":"22419","volume":"34","author":"H Wu","year":"2021","unstructured":"Wu, H., Xu, J., Wang, J., Long, M.: Autoformer: decomposition transformers with auto-correlation for long-term series forecasting. Adv. Neural. Inf. Process. Syst. 34, 22419\u201322430 (2021)","journal-title":"Adv. Neural. Inf. Process. Syst."},{"key":"27_CR18","unstructured":"Zhou, T., et al.: Fedformer: frequency enhanced decomposed transformer for long-term series forecasting. In: International Conference on Machine Learning, pp. 27268\u201327286. PMLR (2022)"},{"key":"27_CR19","unstructured":"Nie, Y.: A time series is worth 64 words: long-term forecasting with transformers. In: The 11th International Conference on Learning Representations (2022)"},{"key":"27_CR20","unstructured":"Cover, T.M.: Elements of information theory. John Wiley & Sons (1999)"},{"key":"27_CR21","unstructured":"Belghazi, M.I.: Mutual information neural estimation. In: International Conference on Machine Learning, pp. 531\u2013540. PMLR (2018)"},{"key":"27_CR22","unstructured":"Poole, B.: On variational bounds of mutual information. In: International Conference on Machine Learning, pp. 5171\u20135180. PMLR (2019)"},{"key":"27_CR23","doi-asserted-by":"publisher","first-page":"1099","DOI":"10.1109\/TIFS.2023.3331239","volume":"19","author":"W Wang","year":"2023","unstructured":"Wang, W., Zhang, C., Tian, Z., Yu, S.: Machine unlearning via representation forgetting with parameter self-sharing. IEEE Trans. Inf. Forensics Secur. 19, 1099\u20131111 (2023)","journal-title":"IEEE Trans. Inf. Forensics Secur."},{"key":"27_CR24","unstructured":"Lin, X., Zhen, H.L., Li, Z., Zhang, Q.F., Kwong, S.: Pareto multi-task learning. In: Advances in Neural Information Processing Systems, p. 32 (2019)"},{"key":"27_CR25","unstructured":"Sener, O., Koltun, V.: Multi-task learning as multi-objective optimization. In: Advances in Neural Information Processing Systems, p. 31 (2018)"},{"issue":"5\u20136","key":"27_CR26","doi-asserted-by":"publisher","first-page":"313","DOI":"10.1016\/j.crma.2012.03.014","volume":"350","author":"JA D\u00e9sid\u00e9ri","year":"2012","unstructured":"D\u00e9sid\u00e9ri, J.A.: Multiple-gradient descent algorithm (MGDA) for multiobjective optimization. C.R. Math. 350(5\u20136), 313\u2013318 (2012)","journal-title":"C.R. Math."},{"key":"27_CR27","doi-asserted-by":"crossref","unstructured":"Warnecke, A., et\u00a0al.: Machine unlearning of features and labels. In: The 30th Network and Distributed System Security Symposium. Internet Society (2023)","DOI":"10.14722\/ndss.2023.23087"},{"key":"27_CR28","doi-asserted-by":"crossref","unstructured":"Kong, Z., Chaudhuri, K.: Data redaction from conditional generative models. In: 2024 IEEE Conference on Secure and Trustworthy Machine Learning (SaTML), pp. 569\u2013591. IEEE (2024)","DOI":"10.1109\/SaTML59370.2024.00035"}],"container-title":["Lecture Notes in Computer Science","Advances in Knowledge Discovery and Data Mining"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-981-92-1462-4_27","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,6,6]],"date-time":"2026-06-06T06:47:05Z","timestamp":1780728425000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-981-92-1462-4_27"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026]]},"ISBN":["9789819214617","9789819214624"],"references-count":28,"URL":"https:\/\/doi.org\/10.1007\/978-981-92-1462-4_27","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"value":"0302-9743","type":"print"},{"value":"1611-3349","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026]]},"assertion":[{"value":"7 June 2026","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"PAKDD","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Pacific-Asia Conference on Knowledge Discovery and Data Mining","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Hong Kong","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"China","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2026","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"9 June 2026","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"12 June 2026","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"30","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"pakdd2026","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/www.pakdd2026.org\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}