{"department":[{"_id":"ChLa"}],"day":"01","publisher":"Neural Information Processing Systems","user_id":"3E5EF7F0-F248-11E8-B48F-1D18A9856A87","file":[{"date_created":"2018-12-12T10:12:42Z","access_level":"open_access","file_name":"IST-2017-775-v1+1_main.pdf","file_id":"4961","creator":"system","date_updated":"2018-12-12T10:12:42Z","content_type":"application/pdf","relation":"main_file","file_size":237111},{"access_level":"open_access","date_created":"2018-12-12T10:12:43Z","content_type":"application/pdf","date_updated":"2018-12-12T10:12:43Z","creator":"system","file_id":"4962","file_name":"IST-2017-775-v1+2_supplementary.pdf","relation":"main_file","file_size":185818}],"language":[{"iso":"eng"}],"publication_status":"published","_id":"1098","scopus_import":1,"oa":1,"volume":29,"abstract":[{"lang":"eng","text":"Better understanding of the potential benefits of information transfer and representation learning is an important step towards the goal of building intelligent systems that are able to persist in the world and learn over time. In this work, we consider a setting where the learner encounters a stream of tasks but is able to retain only limited information from each encountered task, such as a learned predictor. In contrast to most previous works analyzing this scenario, we do not make any distributional assumptions on the task generating process. Instead, we formulate a complexity measure that captures the diversity of the observed tasks. We provide a lifelong learning algorithm with error guarantees for every observed task (rather than on average). We show sample complexity reductions in comparison to solving every task in isolation in terms of our task complexity measure. Further, our algorithmic framework can naturally be viewed as learning a representation from encountered tasks with a neural network."}],"file_date_updated":"2018-12-12T10:12:43Z","date_created":"2018-12-11T11:50:08Z","year":"2016","pubrep_id":"775","ec_funded":1,"month":"12","date_published":"2016-12-01T00:00:00Z","citation":{"ista":"Pentina A, Urner R. 2016. Lifelong learning with weighted majority votes. NIPS: Neural Information Processing Systems, Advances in Neural Information Processing Systems, vol. 29, 3619–3627.","apa":"Pentina, A., &#38; Urner, R. (2016). Lifelong learning with weighted majority votes (Vol. 29, pp. 3619–3627). Presented at the NIPS: Neural Information Processing Systems, Barcelona, Spain: Neural Information Processing Systems.","chicago":"Pentina, Anastasia, and Ruth Urner. “Lifelong Learning with Weighted Majority Votes,” 29:3619–27. Neural Information Processing Systems, 2016.","ama":"Pentina A, Urner R. Lifelong learning with weighted majority votes. In: Vol 29. Neural Information Processing Systems; 2016:3619-3627.","ieee":"A. Pentina and R. Urner, “Lifelong learning with weighted majority votes,” presented at the NIPS: Neural Information Processing Systems, Barcelona, Spain, 2016, vol. 29, pp. 3619–3627.","short":"A. Pentina, R. Urner, in:, Neural Information Processing Systems, 2016, pp. 3619–3627.","mla":"Pentina, Anastasia, and Ruth Urner. <i>Lifelong Learning with Weighted Majority Votes</i>. Vol. 29, Neural Information Processing Systems, 2016, pp. 3619–27."},"intvolume":"        29","project":[{"grant_number":"308036","_id":"2532554C-B435-11E9-9278-68D0E5697425","call_identifier":"FP7","name":"Lifelong Learning of Visual Scene Understanding"}],"quality_controlled":"1","title":"Lifelong learning with weighted majority votes","acknowledgement":"This work was in parts funded by the European Research Council under the European Union’s Seventh Framework Programme (FP7/2007-2013)/ERC grant agreement no 308036.\r\n\r\n","ddc":["006"],"page":"3619-3627","type":"conference","has_accepted_license":"1","date_updated":"2021-01-12T06:48:15Z","publist_id":"6277","oa_version":"Published Version","alternative_title":["Advances in Neural Information Processing Systems"],"conference":{"start_date":"2016-12-05","location":"Barcelona, Spain","name":"NIPS: Neural Information Processing Systems","end_date":"2016-12-10"},"author":[{"first_name":"Anastasia","last_name":"Pentina","full_name":"Pentina, Anastasia","id":"42E87FC6-F248-11E8-B48F-1D18A9856A87"},{"last_name":"Urner","first_name":"Ruth","full_name":"Urner, Ruth"}],"status":"public"}