{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,25]],"date-time":"2026-08-25T10:08:51Z","timestamp":1787652531102,"version":"build-2736575974"},"publisher-location":"New York, NY, USA","reference-count":32,"publisher":"ACM","license":[{"start":{"date-parts":[[2019,7,13]],"date-time":"2019-07-13T00:00:00Z","timestamp":1562976000000},"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":[[2019,7,13]]},"DOI":"10.1145\/3321707.3321845","type":"proceedings-article","created":{"date-parts":[[2019,7,3]],"date-time":"2019-07-03T13:48:04Z","timestamp":1562161684000},"page":"198-206","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":36,"title":["Algorithm selection using deep learning without feature extraction"],"prefix":"10.1145","author":[{"given":"Mohamad","family":"Alissa","sequence":"first","affiliation":[{"name":"Edinburgh Napier University"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Kevin","family":"Sim","sequence":"additional","affiliation":[{"name":"Edinburgh Napier University"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Emma","family":"Hart","sequence":"additional","affiliation":[{"name":"Edinburgh Napier University"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"320","published-online":{"date-parts":[[2019,7,13]]},"reference":[{"key":"e_1_3_2_1_1_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-99259-4_30"},{"key":"e_1_3_2_1_2_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.ejor.2016.04.030"},{"key":"e_1_3_2_1_3_1","volume-title":"Optimal Analysis of Best Fit Bin Packing","author":"D\u00f3sa Gy\u00f6rgy","unstructured":"Gy\u00f6rgy D\u00f3sa and Ji\u0159\u00ed Sgall . 2014. Optimal Analysis of Best Fit Bin Packing . In Automata, Languages, and Programming, Javier Esparza, Pierre Fraigniaud, Thore Husfeldt, and Elias Koutsoupias (Eds.). Springer Berlin Heidelberg , Berlin, Heidelberg , 429--441. Gy\u00f6rgy D\u00f3sa and Ji\u0159\u00ed Sgall. 2014. Optimal Analysis of Best Fit Bin Packing. In Automata, Languages, and Programming, Javier Esparza, Pierre Fraigniaud, Thore Husfeldt, and Elias Koutsoupias (Eds.). Springer Berlin Heidelberg, Berlin, Heidelberg, 429--441."},{"key":"e_1_3_2_1_4_1","volume-title":"The WEKA Workbench. Online Appendix for Data Mining: Practical Machine Learning Tools and Techniques","author":"Eibe Frank","unstructured":"Frank Eibe , A. Hall Mark , and H. Witten Ian . 2016. The WEKA Workbench. Online Appendix for Data Mining: Practical Machine Learning Tools and Techniques ( fourth edition ed.). Morgan Kaufmann . Frank Eibe, A. Hall Mark, and H. Witten Ian. 2016. The WEKA Workbench. Online Appendix for Data Mining: Practical Machine Learning Tools and Techniques (fourth edition ed.). Morgan Kaufmann."},{"key":"e_1_3_2_1_5_1","doi-asserted-by":"publisher","DOI":"10.1109\/ROBOT.1992.220088"},{"key":"e_1_3_2_1_6_1","doi-asserted-by":"crossref","unstructured":"M. R. Garey and D. S. Johnson. 1981. Approximation Algorithms for Bin Packing Problems: A Survey. Springer Vienna Vienna 147--172.  M. R. Garey and D. S. Johnson. 1981. Approximation Algorithms for Bin Packing Problems: A Survey. Springer Vienna Vienna 147--172.","DOI":"10.1007\/978-3-7091-2748-3_8"},{"key":"e_1_3_2_1_7_1","volume-title":"Supervised sequence labelling with recurrent neural networks","author":"Graves Alex","unstructured":"Alex Graves . 2012. Supervised sequence labelling . In Supervised sequence labelling with recurrent neural networks . Springer , 5--13. Alex Graves. 2012. Supervised sequence labelling. In Supervised sequence labelling with recurrent neural networks. Springer, 5--13."},{"key":"e_1_3_2_1_8_1","doi-asserted-by":"publisher","DOI":"10.1162\/neco.1997.9.8.1735"},{"key":"e_1_3_2_1_9_1","volume-title":"Solving a new 3d bin packing problem with deep reinforcement learning method. arXiv preprint arXiv:1708.05930","author":"Hu Haoyuan","year":"2017","unstructured":"Haoyuan Hu , Xiaodong Zhang , Xiaowei Yan , Longfei Wang , and Yinghui Xu. 2017. Solving a new 3d bin packing problem with deep reinforcement learning method. arXiv preprint arXiv:1708.05930 ( 2017 ). Haoyuan Hu, Xiaodong Zhang, Xiaowei Yan, Longfei Wang, and Yinghui Xu. 2017. Solving a new 3d bin packing problem with deep reinforcement learning method. arXiv preprint arXiv:1708.05930 (2017)."},{"key":"e_1_3_2_1_10_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.artint.2013.10.003"},{"key":"e_1_3_2_1_11_1","doi-asserted-by":"publisher","DOI":"10.1137\/0203025"},{"key":"e_1_3_2_1_12_1","volume-title":"Automated Algorithm Selection: Survey and Perspectives. Evolutionary computation","author":"Kerschke Pascal","year":"2018","unstructured":"Pascal Kerschke , Holger H Hoos , Frank Neumann , and Heike Trautmann . 2018. Automated Algorithm Selection: Survey and Perspectives. Evolutionary computation ( 2018 ), 1--47. Pascal Kerschke, Holger H Hoos, Frank Neumann, and Heike Trautmann. 2018. Automated Algorithm Selection: Survey and Perspectives. Evolutionary computation (2018), 1--47."},{"key":"e_1_3_2_1_13_1","volume-title":"Adam: A method for stochastic optimization. arXiv preprint arXiv:1412.6980","author":"Kingma Diederik P","year":"2014","unstructured":"Diederik P Kingma and Jimmy Ba . 2014 . Adam: A method for stochastic optimization. arXiv preprint arXiv:1412.6980 (2014). Diederik P Kingma and Jimmy Ba. 2014. Adam: A method for stochastic optimization. arXiv preprint arXiv:1412.6980 (2014)."},{"key":"e_1_3_2_1_14_1","volume-title":"Algorithm Selection for Combinatorial Search Problems: A Survey","author":"Kotthoff Lars","unstructured":"Lars Kotthoff . 2016. Algorithm Selection for Combinatorial Search Problems: A Survey . Springer International Publishing , Cham , 149--190. Lars Kotthoff. 2016. Algorithm Selection for Combinatorial Search Problems: A Survey. Springer International Publishing, Cham, 149--190."},{"key":"e_1_3_2_1_15_1","volume-title":"The measurement of observer agreement for categorical data. biometrics","author":"Richard Landis J","year":"1977","unstructured":"J Richard Landis and Gary G Koch . 1977. The measurement of observer agreement for categorical data. biometrics ( 1977 ), 159--174. J Richard Landis and Gary G Koch. 1977. The measurement of observer agreement for categorical data. biometrics (1977), 159--174."},{"key":"e_1_3_2_1_16_1","volume-title":"A critical review of recurrent neural networks for sequence learning. arXiv preprint arXiv:1506.00019","author":"Lipton Zachary C","year":"2015","unstructured":"Zachary C Lipton , John Berkowitz , and Charles Elkan . 2015. A critical review of recurrent neural networks for sequence learning. arXiv preprint arXiv:1506.00019 ( 2015 ). Zachary C Lipton, John Berkowitz, and Charles Elkan. 2015. A critical review of recurrent neural networks for sequence learning. arXiv preprint arXiv:1506.00019 (2015)."},{"key":"e_1_3_2_1_17_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.ijpe.2013.04.041"},{"key":"e_1_3_2_1_18_1","doi-asserted-by":"publisher","DOI":"10.1109\/BigDataService.2017.18"},{"key":"e_1_3_2_1_19_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-540-30201-8_33"},{"key":"e_1_3_2_1_20_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICTAI.2014.18"},{"key":"e_1_3_2_1_21_1","doi-asserted-by":"publisher","DOI":"10.1145\/3234150"},{"key":"e_1_3_2_1_22_1","volume-title":"Advances in Computers, Morris Rubinoff and Marshall C","author":"Rice John R","unstructured":"John R Rice . 1976. The Algorithm Selection Problem . In Advances in Computers, Morris Rubinoff and Marshall C . Yovits (Eds.). Vol. 15 . Elsevier , 65 -- 118. John R Rice. 1976. The Algorithm Selection Problem. In Advances in Computers, Morris Rubinoff and Marshall C. Yovits (Eds.). Vol. 15. Elsevier, 65 -- 118."},{"key":"e_1_3_2_1_23_1","volume-title":"Proceedings of the 4th Annual Conference on Genetic and Evolutionary Computation. Morgan Kaufmann Publishers Inc., 942--948","author":"Ross Peter","year":"2002","unstructured":"Peter Ross , Sonia Schulenburg , Javier G Mar\u00edn-Bl\u00e4zquez , and Emma Hart . 2002 . Hyper-heuristics: learning to combine simple heuristics in bin-packing problems . In Proceedings of the 4th Annual Conference on Genetic and Evolutionary Computation. Morgan Kaufmann Publishers Inc., 942--948 . Peter Ross, Sonia Schulenburg, Javier G Mar\u00edn-Bl\u00e4zquez, and Emma Hart. 2002. Hyper-heuristics: learning to combine simple heuristics in bin-packing problems. In Proceedings of the 4th Annual Conference on Genetic and Evolutionary Computation. Morgan Kaufmann Publishers Inc., 942--948."},{"key":"e_1_3_2_1_24_1","doi-asserted-by":"publisher","DOI":"10.1016\/S0305-0548(96)00082-2"},{"key":"e_1_3_2_1_25_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-642-32964-7_35"},{"key":"e_1_3_2_1_26_1","doi-asserted-by":"publisher","DOI":"10.1162\/EVCO_a_00121"},{"key":"e_1_3_2_1_27_1","volume-title":"Introduction to Deep Learning: From Logical Calculus to Artificial Intelligence","author":"Skansi Sandro","unstructured":"Sandro Skansi . 2018. Introduction to Deep Learning: From Logical Calculus to Artificial Intelligence . Springer . Sandro Skansi. 2018. Introduction to Deep Learning: From Logical Calculus to Artificial Intelligence. Springer."},{"key":"e_1_3_2_1_28_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.cor.2013.11.015"},{"key":"e_1_3_2_1_29_1","doi-asserted-by":"publisher","DOI":"10.1007\/s10472-011-9230-5"},{"key":"e_1_3_2_1_30_1","doi-asserted-by":"publisher","DOI":"10.1145\/1456650.1456656"},{"key":"e_1_3_2_1_31_1","volume-title":"On the origin of deep learning. arXiv preprint arXiv:1702.07800","author":"Wang Haohan","year":"2017","unstructured":"Haohan Wang and Bhiksha Raj . 2017. On the origin of deep learning. arXiv preprint arXiv:1702.07800 ( 2017 ). Haohan Wang and Bhiksha Raj. 2017. On the origin of deep learning. arXiv preprint arXiv:1702.07800 (2017)."},{"key":"e_1_3_2_1_32_1","doi-asserted-by":"publisher","DOI":"10.1162\/evco.1995.3.2.149"}],"event":{"name":"GECCO '19: Genetic and Evolutionary Computation Conference","location":"Prague Czech Republic","acronym":"GECCO '19","sponsor":["SIGEVO ACM Special Interest Group on Genetic and Evolutionary Computation"]},"container-title":["Proceedings of the Genetic and Evolutionary Computation Conference"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3321707.3321845","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3321707.3321845","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,18]],"date-time":"2025-06-18T00:25:29Z","timestamp":1750206329000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3321707.3321845"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019,7,13]]},"references-count":32,"alternative-id":["10.1145\/3321707.3321845","10.1145\/3321707"],"URL":"https:\/\/doi.org\/10.1145\/3321707.3321845","relation":{},"subject":[],"published":{"date-parts":[[2019,7,13]]},"assertion":[{"value":"2019-07-13","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}