{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,8,23]],"date-time":"2025-08-23T05:15:06Z","timestamp":1755926106672,"version":"3.41.0"},"publisher-location":"New York, NY, USA","reference-count":18,"publisher":"ACM","license":[{"start":{"date-parts":[[2017,8,13]],"date-time":"2017-08-13T00:00:00Z","timestamp":1502582400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2017,8,13]]},"DOI":"10.1145\/3097983.3098157","type":"proceedings-article","created":{"date-parts":[[2017,8,4]],"date-time":"2017-08-04T18:35:54Z","timestamp":1501871754000},"page":"1783-1792","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":9,"title":["AESOP"],"prefix":"10.1145","author":[{"given":"Supratim","family":"Deb","sequence":"first","affiliation":[{"name":"AT&T Labs, Bedminister, NJ, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zihui","family":"Ge","sequence":"additional","affiliation":[{"name":"AT&T Labs, Bedminister, NJ, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Sastry","family":"Isukapalli","sequence":"additional","affiliation":[{"name":"AT&T Labs, Bedminister, NJ, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Sarat","family":"Puthenpura","sequence":"additional","affiliation":[{"name":"AT&T Labs, Bedminister, NJ, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Shobha","family":"Venkataraman","sequence":"additional","affiliation":[{"name":"AT&T Labs, Bedminister, NJ, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"He","family":"Yan","sequence":"additional","affiliation":[{"name":"AT&T Labs, Bedminister, NJ, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jennifer","family":"Yates","sequence":"additional","affiliation":[{"name":"AT&T Labs, Bedminister, NJ, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","published-online":{"date-parts":[[2017,8,13]]},"reference":[{"key":"e_1_3_2_1_1_1","doi-asserted-by":"publisher","DOI":"10.1145\/637201.637210"},{"key":"e_1_3_2_1_2_1","volume-title":"Predicting Disk Replacement Towards Reliable Data Centers Proceedings of the 22Nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD'16)","author":"Botezatu Mirela Madalina","year":"2016","unstructured":"Mirela Madalina Botezatu , Ioana Giurgiu , Jasmina Bogojeska , and Dorothea Wiesmann 2016 . Predicting Disk Replacement Towards Reliable Data Centers Proceedings of the 22Nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD'16) . ACM, New York, NY, USA, 39--48. Mirela Madalina Botezatu, Ioana Giurgiu, Jasmina Bogojeska, and Dorothea Wiesmann 2016. Predicting Disk Replacement Towards Reliable Data Centers Proceedings of the 22Nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD'16). ACM, New York, NY, USA, 39--48."},{"key":"e_1_3_2_1_3_1","doi-asserted-by":"publisher","DOI":"10.1017\/CBO9780511804441"},{"key":"e_1_3_2_1_4_1","volume-title":"OSDI","volume":"4","author":"Cohen Ira","year":"2004","unstructured":"Ira Cohen , Jeffrey S Chase , Moises Goldszmidt , Terence Kelly , and Julie Symons 2004 . Correlating Instrumentation Data to System States: A Building Block for Automated Diagnosis and Control .. In OSDI , Vol. Vol. 4 . 16--16. Ira Cohen, Jeffrey S Chase, Moises Goldszmidt, Terence Kelly, and Julie Symons 2004. Correlating Instrumentation Data to System States: A Building Block for Automated Diagnosis and Control.. In OSDI, Vol. Vol. 4. 16--16."},{"key":"e_1_3_2_1_5_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.patrec.2005.10.010"},{"key":"e_1_3_2_1_6_1","volume-title":"et almbox","author":"Friedman Jerome","year":"2000","unstructured":"Jerome Friedman , Trevor Hastie , Robert Tibshirani , et almbox . 2000 . Additive logistic regression: a statistical view of boosting (with discussion and a rejoinder by the authors). The annals of statistics Vol. 28 , 2 (2000), 337--407. Jerome Friedman, Trevor Hastie, Robert Tibshirani, et almbox. 2000. Additive logistic regression: a statistical view of boosting (with discussion and a rejoinder by the authors). The annals of statistics Vol. 28, 2 (2000), 337--407."},{"key":"e_1_3_2_1_7_1","doi-asserted-by":"crossref","unstructured":"Ramesh Govindan Ina Minei Mahesh Kallahalla Bikash Koley and Amin Vahdat 2016. Evolve or Die: High-Availability Design Principles Drawn from Googles Network Infrastructure Proceedings of the 2016 conference on ACM SIGCOMM 2016 Conference. ACM 58--72.  Ramesh Govindan Ina Minei Mahesh Kallahalla Bikash Koley and Amin Vahdat 2016. Evolve or Die: High-Availability Design Principles Drawn from Googles Network Infrastructure Proceedings of the 2016 conference on ACM SIGCOMM 2016 Conference. ACM 58--72.","DOI":"10.1145\/2934872.2934891"},{"volume-title":"Detecting anomalies in network traffic using maximum entropy estimation Proceedings of the 5th ACM SIGCOMM conference on Internet Measurement","author":"Gu Yu","key":"e_1_3_2_1_8_1","unstructured":"Yu Gu , Andrew McCallum , and Don Towsley 2005. Detecting anomalies in network traffic using maximum entropy estimation Proceedings of the 5th ACM SIGCOMM conference on Internet Measurement . USENIX Association , 32--32. Yu Gu, Andrew McCallum, and Don Towsley 2005. Detecting anomalies in network traffic using maximum entropy estimation Proceedings of the 5th ACM SIGCOMM conference on Internet Measurement. USENIX Association, 32--32."},{"key":"e_1_3_2_1_9_1","doi-asserted-by":"publisher","DOI":"10.1145\/1015467.1015492"},{"key":"e_1_3_2_1_10_1","doi-asserted-by":"publisher","DOI":"10.1145\/2535372.2535382"},{"key":"e_1_3_2_1_11_1","volume-title":"Detecting the Performance Impact of Upgrades in Large Operational Networks Proceedings of the ACM SIGCOMM 2010 Conference (SIGCOMM'10)","author":"Mahimkar Ajay Anil","year":"2010","unstructured":"Ajay Anil Mahimkar , Han Hee Song , Zihui Ge , Aman Shaikh , Jia Wang , Jennifer Yates , Yin Zhang , and Joanne Emmons 2010 . Detecting the Performance Impact of Upgrades in Large Operational Networks Proceedings of the ACM SIGCOMM 2010 Conference (SIGCOMM'10) . ACM, New York, NY, USA, 303--314. Ajay Anil Mahimkar, Han Hee Song, Zihui Ge, Aman Shaikh, Jia Wang, Jennifer Yates, Yin Zhang, and Joanne Emmons 2010. Detecting the Performance Impact of Upgrades in Large Operational Networks Proceedings of the ACM SIGCOMM 2010 Conference (SIGCOMM'10). ACM, New York, NY, USA, 303--314."},{"key":"e_1_3_2_1_12_1","volume-title":"Resource Management with Deep Reinforcement Learning Proceedings of the 15th ACM Workshop on Hot Topics in Networks (HotNets'16)","author":"Mao Hongzi","year":"2016","unstructured":"Hongzi Mao , Mohammad Alizadeh , Ishai Menache , and Srikanth Kandula 2016 . Resource Management with Deep Reinforcement Learning Proceedings of the 15th ACM Workshop on Hot Topics in Networks (HotNets'16) . ACM, New York, NY, USA, 50--56. Hongzi Mao, Mohammad Alizadeh, Ishai Menache, and Srikanth Kandula 2016. Resource Management with Deep Reinforcement Learning Proceedings of the 15th ACM Workshop on Hot Topics in Networks (HotNets'16). ACM, New York, NY, USA, 50--56."},{"key":"e_1_3_2_1_13_1","doi-asserted-by":"publisher","DOI":"10.1109\/INFCOM.2004.1354653"},{"key":"e_1_3_2_1_14_1","doi-asserted-by":"publisher","DOI":"10.1111\/j.1467-9868.2010.00740.x"},{"key":"e_1_3_2_1_15_1","volume-title":"ACM","author":"Nair Vinod","year":"2015","unstructured":"Vinod Nair , Ameya Raul , Shwetabh Khanduja , Vikas Bahirwani , Qihong Shao , Sundararajan Sellamanickam , Sathiya Keerthi , Steve Herbert , and Sudheer Dhulipalla 2015 . Learning a Hierarchical Monitoring System for Detecting and Diagnosing Service Issues Proceedings of the 21th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD'15) . ACM , New York, NY, USA , 2029--2038. Vinod Nair, Ameya Raul, Shwetabh Khanduja, Vikas Bahirwani, Qihong Shao, Sundararajan Sellamanickam, Sathiya Keerthi, Steve Herbert, and Sudheer Dhulipalla 2015. Learning a Hierarchical Monitoring System for Detecting and Diagnosing Service Issues Proceedings of the 21th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD'15). ACM, New York, NY, USA, 2029--2038."},{"key":"e_1_3_2_1_16_1","volume-title":"Anomaly Detection Using Program Control Flow Graph Mining From Execution Logs Proceedings of the 22Nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD'16)","author":"Nandi Animesh","year":"2016","unstructured":"Animesh Nandi , Atri Mandal , Shubham Atreja , Gargi B. Dasgupta , and Subhrajit Bhattacharya . 2016 . Anomaly Detection Using Program Control Flow Graph Mining From Execution Logs Proceedings of the 22Nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD'16) . ACM, New York, NY, USA, 215--224. Animesh Nandi, Atri Mandal, Shubham Atreja, Gargi B. Dasgupta, and Subhrajit Bhattacharya. 2016. Anomaly Detection Using Program Control Flow Graph Mining From Execution Logs Proceedings of the 22Nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD'16). ACM, New York, NY, USA, 215--224."},{"key":"e_1_3_2_1_17_1","doi-asserted-by":"publisher","DOI":"10.1109\/TSP.2003.814797"},{"key":"e_1_3_2_1_18_1","doi-asserted-by":"publisher","DOI":"10.1109\/TNET.2012.2188837"}],"event":{"name":"KDD '17: The 23rd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining","sponsor":["SIGMOD ACM Special Interest Group on Management of Data","SIGKDD ACM Special Interest Group on Knowledge Discovery in Data"],"location":"Halifax NS Canada","acronym":"KDD '17"},"container-title":["Proceedings of the 23rd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3097983.3098157","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3097983.3098157","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,18]],"date-time":"2025-06-18T03:30:02Z","timestamp":1750217402000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3097983.3098157"}},"subtitle":["Automatic Policy Learning for Predicting and Mitigating Network Service Impairments"],"short-title":[],"issued":{"date-parts":[[2017,8,13]]},"references-count":18,"alternative-id":["10.1145\/3097983.3098157","10.1145\/3097983"],"URL":"https:\/\/doi.org\/10.1145\/3097983.3098157","relation":{},"subject":[],"published":{"date-parts":[[2017,8,13]]},"assertion":[{"value":"2017-08-13","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}