Article PDF
Avoid common mistakes on your manuscript.
References
Chen Z Y, Ma N Z, Liu B. Lifelong learning for sentiment classification. In: Proceedings of ACL Conference. 2015
Pan S J, Yang Q. A survey on transfer learning. IEEE Transaction on Knowledge and Data Engineering, 2010, 22(10): 1345–1359
Caruana R. Multitask learning. Machine Learning, 1997, 28(1)
Thrun S, Mitchell T M. Lifelong robot learning. In: Steels L, ed. The Biology and Technology of Intelligent Autonomous Agents. Berlin: Springer, 1995, 165–196
Thrun S. Is learning the n-th thing any easier than learning the first? Advances in Neural Information Processing Systems, 1996: 640–646
Silver D L, Mercer R E. The task rehearsal method of life-long learning: overcoming impoverished data. In: Proceedings of the 15th Conference of the Canadian Society for Computational Studies of Intelligence on Advances in Artificial Intelligence. 2002, 90–101
Fei G L, Wang S, Liu B. Learning cumulatively to become more knowledgeable. In: Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. 2016, 1565–1574
Ruvolo P, Eaton E. ELLA: an efficient lifelong learning algorithm. In: Proceedings of International Conference on Machine Learning. 2013, 507–515
Pentina A, Lampert C H. A PAC-Bayesian bound for lifelong learning. In: Proceedings of International Conference on Machine Learning. 2014, 991–999
Chen Z Y, Liu B. Topic modeling using topics from many domains, lifelong learning and big data. In: Proceedings of International Conference on Machine Learning. 2014
Liu Q, Liu B, Zhang Y L, Kim D S, Gao Z Q. Improving opinion aspect extraction using semantic similarity and aspect associations. In: Proceedings of the 30th AAAI Conference on Artificial Intelligence. 2016
Shu L, Liu B, Xu H, Kim A. Separating entities and aspects in opinion targets using lifelong graph labeling. In: Proceedings of Conference on Empirical Methods in Natural Language Processing, 2016
Mitchell T, Cohen W, Hruschka E, Talukdar P, Betteridge J, Carlson A, Dalvi B, Gardner M, Kisiel B, Krishnamurthy J, Lao N, Mazaitis K, Mohamed T, Nakashole N, Platanios E, Ritter A, Samadi M, Settles B, Wang R, Wijaya D, Gupta A, Chen X, Saparov A, Greaves M, Welling J. Never-ending learning. In: Proceedings of the 29th AAAI Conference on Artificial Intelligence. 2015, 2302–2310
Tanaka F, Yamamura M. An approach to lifelong reinforcement learning through multiple environments. In: Proceedings of the 6th European Workshop on Learning Robots. 1997, 93–99
Bou Ammar H, Eaton E, Ruvolo P, Taylor M. Online multi-task learning for policy gradient methods. In: Proceedings of the 31st International Conference on Machine Learning. 2014, 1206–1214
Acknowledgements
This work was supported in part by a grant from National Science Foundation (NSF) (IIS-1407927), a grant from NCI (R01CA192240), and a gift from Bosch.
Author information
Authors and Affiliations
Corresponding author
Additional information
Bing Liu is a professor of computer science at University of Illinois at Chicago, USA. His research interests include sentiment analysis and opinion mining, lifelong machine learning, data mining, machine learning, and natural language processing. He currently serves as the Chair of ACM SIGKDD. He is an ACM Fellow, AAAI Fellow, and IEEE Fellow.
Rights and permissions
About this article
Cite this article
Liu, B. Lifelong machine learning: a paradigm for continuous learning. Front. Comput. Sci. 11, 359–361 (2017). https://doi.org/10.1007/s11704-016-6903-6
Published:
Issue Date:
DOI: https://doi.org/10.1007/s11704-016-6903-6