{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,29]],"date-time":"2026-04-29T20:49:12Z","timestamp":1777495752758,"version":"3.51.4"},"publisher-location":"New York, NY, USA","reference-count":35,"publisher":"ACM","license":[{"start":{"date-parts":[[2019,7,25]],"date-time":"2019-07-25T00:00:00Z","timestamp":1564012800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"funder":[{"DOI":"10.13039\/100006642","name":"U.S. Department of Education","doi-asserted-by":"publisher","award":["P200A150306"],"award-info":[{"award-number":["P200A150306"]}],"id":[{"id":"10.13039\/100006642","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Worcester Polytechnic Institute","award":["Arvid Anderson Fellowship"],"award-info":[{"award-number":["Arvid Anderson Fellowship"]}]},{"DOI":"10.13039\/100000001","name":"National Science Foundation","doi-asserted-by":"publisher","award":["IIS-1815866,CNS-1852498,CNS-1560229,IIS-1718310"],"award-info":[{"award-number":["IIS-1815866,CNS-1852498,CNS-1560229,IIS-1718310"]}],"id":[{"id":"10.13039\/100000001","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2019,7,25]]},"DOI":"10.1145\/3292500.3330974","type":"proceedings-article","created":{"date-parts":[[2019,7,26]],"date-time":"2019-07-26T13:17:26Z","timestamp":1564147046000},"page":"101-110","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":33,"title":["Adaptive-Halting Policy Network for Early Classification"],"prefix":"10.1145","author":[{"given":"Thomas","family":"Hartvigsen","sequence":"first","affiliation":[{"name":"Worcester Polytechnic Institute, Worcester, MA, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Cansu","family":"Sen","sequence":"additional","affiliation":[{"name":"Worcester Polytechnic Institute, Worcester, MA, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xiangnan","family":"Kong","sequence":"additional","affiliation":[{"name":"Worcester Polytechnic Institute, Worcester, MA, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Elke","family":"Rundensteiner","sequence":"additional","affiliation":[{"name":"Worcester Polytechnic Institute, Worcester, MA, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","published-online":{"date-parts":[[2019,7,25]]},"reference":[{"key":"e_1_3_2_1_1_1","doi-asserted-by":"publisher","DOI":"10.1103\/PhysRevE.64.061907"},{"key":"e_1_3_2_1_2_1","volume-title":"arXiv","author":"Bengio Yoshua","year":"2013"},{"key":"e_1_3_2_1_3_1","unstructured":"John S Bridle. 1990. Training stochastic model recognition algorithms as networks can lead to maximum mutual information estimation of parameters. In NeurIPS .   John S Bridle. 1990. Training stochastic model recognition algorithms as networks can lead to maximum mutual information estimation of parameters. In NeurIPS ."},{"key":"e_1_3_2_1_4_1","volume-title":"Caglar Gulcehre, Dzmitry Bahdanau, Fethi Bougares, Holger Schwenk, and Yoshua Bengio.","author":"Cho Kyunghyun","year":"2014"},{"key":"e_1_3_2_1_5_1","volume-title":"arXiv","author":"Dan Cirecs","year":"2012"},{"key":"e_1_3_2_1_6_1","doi-asserted-by":"crossref","unstructured":"Martinez Coralie Guillaume Perrin E Ramasso and Rombaut Mich\u00e8lle. 2018. A deep reinforcement learning approach for earlyclassification of time series. In EUSIPCO .  Martinez Coralie Guillaume Perrin E Ramasso and Rombaut Mich\u00e8lle. 2018. A deep reinforcement learning approach for earlyclassification of time series. In EUSIPCO .","DOI":"10.23919\/EUSIPCO.2018.8553544"},{"key":"e_1_3_2_1_7_1","volume-title":"Finding structure in time. Cognitive science","author":"Elman Jeffrey L","year":"1990"},{"key":"e_1_3_2_1_8_1","doi-asserted-by":"publisher","DOI":"10.1186\/1471-2105-13-195"},{"key":"e_1_3_2_1_9_1","volume-title":"Extraction of interpretable multivariate patterns for early diagnostics","author":"Ghalwash Mohamed F"},{"key":"e_1_3_2_1_10_1","doi-asserted-by":"publisher","DOI":"10.1145\/2623330.2623694"},{"key":"e_1_3_2_1_11_1","volume-title":"arXiv","author":"Graves Alex","year":"2013"},{"key":"e_1_3_2_1_12_1","doi-asserted-by":"crossref","volume-title":"Speech recognition with deep recurrent neural networks","author":"Graves Alex","DOI":"10.1109\/ICASSP.2013.6638947"},{"key":"e_1_3_2_1_13_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2014.07.056"},{"key":"e_1_3_2_1_14_1","doi-asserted-by":"publisher","DOI":"10.1162\/neco.1997.9.8.1735"},{"key":"e_1_3_2_1_15_1","doi-asserted-by":"publisher","DOI":"10.1145\/3132847.3132947"},{"key":"e_1_3_2_1_16_1","volume-title":"Leo Anthony Celi, and Roger G Mark","author":"Johnson Alistair EW","year":"2016"},{"key":"e_1_3_2_1_17_1","unstructured":"Francc ois Kawala Ahlame Douzal-Chouakria Eric Gaussier and Eustache Dimert. 2013. Pr\u00e9dictions d'activit\u00e9 dans les r\u00e9seaux sociaux en ligne. In 4i\u00e8me conf\u00e9rence sur les mod\u00e8les et l'analyse des r\u00e9seaux: Approches math\u00e9matiques et informatiques. 16.  Francc ois Kawala Ahlame Douzal-Chouakria Eric Gaussier and Eustache Dimert. 2013. Pr\u00e9dictions d'activit\u00e9 dans les r\u00e9seaux sociaux en ligne. In 4i\u00e8me conf\u00e9rence sur les mod\u00e8les et l'analyse des r\u00e9seaux: Approches math\u00e9matiques et informatiques. 16."},{"key":"e_1_3_2_1_18_1","volume-title":"Adam: A method for stochastic optimization. In ICLR .","author":"Kingma Diederik P","year":"2014"},{"key":"e_1_3_2_1_19_1","doi-asserted-by":"crossref","unstructured":"Yu-Feng Lin Hsuan-Hsu Chen Vincent S Tseng and Jian Pei. 2015. Reliable early classification on multivariate time series with numerical and categorical attributes. In PAKDD. 199--211.  Yu-Feng Lin Hsuan-Hsu Chen Vincent S Tseng and Jian Pei. 2015. Reliable early classification on multivariate time series with numerical and categorical attributes. In PAKDD. 199--211.","DOI":"10.1007\/978-3-319-18038-0_16"},{"key":"e_1_3_2_1_20_1","volume-title":"Learning activity progression in lstms for activity detection and early detection","author":"Ma Shugao","year":"1942"},{"key":"e_1_3_2_1_21_1","volume-title":"Jan vC ernock, and Sanjeev Khudanpur","author":"Mikolov Tom\u00e1vs","year":"2010"},{"key":"e_1_3_2_1_22_1","unstructured":"Volodymyr Mnih Nicolas Heess Alex Graves and Koray Kavukcuoglu. 2014. Recurrent models of visual attention. In NeurIPS. 2204--2212.   Volodymyr Mnih Nicolas Heess Alex Graves and Koray Kavukcuoglu. 2014. Recurrent models of visual attention. In NeurIPS. 2204--2212."},{"key":"e_1_3_2_1_23_1","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2017.2764939"},{"key":"e_1_3_2_1_24_1","doi-asserted-by":"publisher","DOI":"10.1007\/s10618-016-0462-1"},{"key":"e_1_3_2_1_25_1","volume-title":"arXiv","author":"Schmidhuber J\u00fcrgen","year":"2012"},{"key":"e_1_3_2_1_26_1","unstructured":"John Schulman Nicolas Heess Theophane Weber and Pieter Abbeel. 2015. Gradient estimation using stochastic computation graphs. In NeurIPS. 3528--3536.   John Schulman Nicolas Heess Theophane Weber and Pieter Abbeel. 2015. Gradient estimation using stochastic computation graphs. In NeurIPS. 3528--3536."},{"key":"e_1_3_2_1_27_1","unstructured":"Richard S Sutton David A McAllester Satinder P Singh and Yishay Mansour. 2000. Policy gradient methods for reinforcement learning with function approximation. In NeurIPS. 1057--1063.   Richard S Sutton David A McAllester Satinder P Singh and Yishay Mansour. 2000. Policy gradient methods for reinforcement learning with function approximation. In NeurIPS. 1057--1063."},{"key":"e_1_3_2_1_28_1","volume-title":"Lstm-based early recognition of motion patterns","author":"Weber Markus"},{"key":"e_1_3_2_1_29_1","unstructured":"Jenna Wiens Eric Horvitz and John V Guttag. 2012. Patient risk stratification for hospital-associated c. diff as a time-series classification task. In NeurIPS. 467--475.   Jenna Wiens Eric Horvitz and John V Guttag. 2012. Patient risk stratification for hospital-associated c. diff as a time-series classification task. In NeurIPS. 467--475."},{"key":"e_1_3_2_1_30_1","doi-asserted-by":"publisher","DOI":"10.1007\/BF00992696"},{"key":"e_1_3_2_1_31_1","unstructured":"Zhengzheng Xing Jian Pei and Phillip Yu. 2009. Early Prediction on Time Series: A Nearest Neighbor Approach. In IJCAI. 1297--1302.   Zhengzheng Xing Jian Pei and Phillip Yu. 2009. Early Prediction on Time Series: A Nearest Neighbor Approach. In IJCAI. 1297--1302."},{"key":"e_1_3_2_1_32_1","doi-asserted-by":"publisher","DOI":"10.5555\/3225640.3225814"},{"key":"e_1_3_2_1_33_1","unstructured":"Zhengzheng Xing Jian Pei Philip S Yu and Ke Wang. 2011. Extracting interpretable features for early classification on time series. In SDM . 247--258.  Zhengzheng Xing Jian Pei Philip S Yu and Ke Wang. 2011. Extracting interpretable features for early classification on time series. In SDM . 247--258."},{"key":"e_1_3_2_1_34_1","unstructured":"Kelvin Xu Jimmy Ba Ryan Kiros Kyunghyun Cho Aaron Courville Ruslan Salakhudinov Rich Zemel and Yoshua Bengio. 2015. Show attend and tell: Neural image caption generation with visual attention. In ICML . 2048--2057.   Kelvin Xu Jimmy Ba Ryan Kiros Kyunghyun Cho Aaron Courville Ruslan Salakhudinov Rich Zemel and Yoshua Bengio. 2015. Show attend and tell: Neural image caption generation with visual attention. In ICML . 2048--2057."},{"key":"e_1_3_2_1_35_1","doi-asserted-by":"publisher","DOI":"10.1145\/1557019.1557122"}],"event":{"name":"KDD '19: The 25th ACM SIGKDD Conference on Knowledge Discovery and Data Mining","location":"Anchorage AK USA","acronym":"KDD '19","sponsor":["SIGMOD ACM Special Interest Group on Management of Data","SIGKDD ACM Special Interest Group on Knowledge Discovery in Data"]},"container-title":["Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3292500.3330974","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3292500.3330974","content-type":"application\/pdf","content-version":"vor","intended-application":"syndication"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3292500.3330974","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,18]],"date-time":"2025-06-18T00:26:04Z","timestamp":1750206364000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3292500.3330974"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019,7,25]]},"references-count":35,"alternative-id":["10.1145\/3292500.3330974","10.1145\/3292500"],"URL":"https:\/\/doi.org\/10.1145\/3292500.3330974","relation":{},"subject":[],"published":{"date-parts":[[2019,7,25]]},"assertion":[{"value":"2019-07-25","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}