{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,4,5]],"date-time":"2025-04-05T10:45:14Z","timestamp":1743849914070,"version":"3.40.3"},"publisher-location":"Cham","reference-count":48,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783030457709"},{"type":"electronic","value":"9783030457716"}],"license":[{"start":{"date-parts":[[2020,1,1]],"date-time":"2020-01-01T00:00:00Z","timestamp":1577836800000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2020]]},"DOI":"10.1007\/978-3-030-45771-6_33","type":"book-chapter","created":{"date-parts":[[2020,4,13]],"date-time":"2020-04-13T21:03:32Z","timestamp":1586811812000},"page":"433-447","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":10,"title":["On the Convexification of Constrained Quadratic Optimization Problems with Indicator Variables"],"prefix":"10.1007","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-1522-4501","authenticated-orcid":false,"given":"Linchuan","family":"Wei","sequence":"first","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3668-0653","authenticated-orcid":false,"given":"Andr\u00e9s","family":"G\u00f3mez","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6548-9378","authenticated-orcid":false,"given":"Simge","family":"K\u00fc\u00e7\u00fckyavuz","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2020,4,14]]},"reference":[{"issue":"3","key":"33_CR1","doi-asserted-by":"publisher","first-page":"187","DOI":"10.1016\/j.orl.2008.12.009","volume":"37","author":"MS Akt\u00fcrk","year":"2009","unstructured":"Akt\u00fcrk, M.S., Atamt\u00fcrk, A., G\u00fcrel, S.: A strong conic quadratic reformulation for machine-job assignment with controllable processing times. Oper. Res. Lett. 37(3), 187\u2013191 (2009)","journal-title":"Oper. Res. Lett."},{"issue":"2","key":"33_CR2","doi-asserted-by":"publisher","first-page":"233","DOI":"10.1007\/s10107-012-0602-3","volume":"136","author":"KM Anstreicher","year":"2012","unstructured":"Anstreicher, K.M.: On convex relaxations for quadratically constrained quadratic programming. Math. Program. 136(2), 233\u2013251 (2012). https:\/\/doi.org\/10.1007\/s10107-012-0602-3","journal-title":"Math. Program."},{"issue":"1","key":"33_CR3","doi-asserted-by":"publisher","first-page":"141","DOI":"10.1007\/s10107-018-1301-5","volume":"170","author":"A Atamt\u00fcrk","year":"2018","unstructured":"Atamt\u00fcrk, A., G\u00f3mez, A.: Strong formulations for quadratic optimization with M-matrices and indicator variables. Math. Program. 170(1), 141\u2013176 (2018). https:\/\/doi.org\/10.1007\/s10107-018-1301-5","journal-title":"Math. Program."},{"key":"33_CR4","unstructured":"Atamt\u00fcrk, A., G\u00f3mez, A.: Rank-one convexification for sparse regression (2019). http:\/\/www.optimization-online.org\/DB_HTML\/2019\/01\/7050.html"},{"key":"33_CR5","unstructured":"Atamt\u00fcrk, A., G\u00f3mez, A., Han, S.: Sparse and smooth signal estimation: convexification of L0 formulations (2018). http:\/\/www.optimization-online.org\/DB_HTML\/2018\/11\/6948.html"},{"key":"33_CR6","unstructured":"Bacci, T., Frangioni, A., Gentile, C., Tavlaridis-Gyparakis, K.: New MINLP formulations for the unit commitment problems with ramping constraints. Optimization (2019). http:\/\/www.optimization-online.org\/DB_FILE\/2019\/10\/7426.pdf"},{"key":"33_CR7","series-title":"Springer Proceedings in Mathematics & Statistics","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1007\/978-3-319-17689-5_1","volume-title":"Numerical Analysis and Optimization","author":"P Belotti","year":"2015","unstructured":"Belotti, P., G\u00f3ez, J.C., P\u00f3lik, I., Ralphs, T.K., Terlaky, T.: A conic representation of the convex hull of disjunctive sets and conic cuts for integer second order cone optimization. In: Al-Baali, M., Grandinetti, L., Purnama, A. (eds.) Numerical Analysis and Optimization. SPMS, vol. 134, pp. 1\u201335. Springer, Cham (2015). https:\/\/doi.org\/10.1007\/978-3-319-17689-5_1"},{"key":"33_CR8","unstructured":"Bertsimas, D., Cory-Wright, R., Pauphilet, J.: A unified approach to mixed-integer optimization: nonlinear formulations and scalable algorithms. arXiv preprint arXiv:1907.02109 (2019)"},{"issue":"1","key":"33_CR9","doi-asserted-by":"publisher","first-page":"2","DOI":"10.1287\/opre.2015.1436","volume":"64","author":"D Bertsimas","year":"2016","unstructured":"Bertsimas, D., King, A.: OR forum - an algorithmic approach to linear regression. Oper. Res. 64(1), 2\u201316 (2016)","journal-title":"Oper. Res."},{"issue":"2","key":"33_CR10","doi-asserted-by":"publisher","first-page":"813","DOI":"10.1214\/15-AOS1388","volume":"44","author":"D Bertsimas","year":"2016","unstructured":"Bertsimas, D., King, A., Mazumder, R.: Best subset selection via a modern optimization lens. Ann. Stat. 44(2), 813\u2013852 (2016)","journal-title":"Ann. Stat."},{"issue":"3","key":"33_CR11","doi-asserted-by":"publisher","first-page":"1111","DOI":"10.1214\/13-AOS1096","volume":"41","author":"J Bien","year":"2013","unstructured":"Bien, J., Taylor, J., Tibshirani, R.: A lasso for hierarchical interactions. Ann. Stat. 41(3), 1111 (2013)","journal-title":"Ann. Stat."},{"issue":"2","key":"33_CR12","doi-asserted-by":"publisher","first-page":"643","DOI":"10.1137\/120878963","volume":"24","author":"D Bienstock","year":"2014","unstructured":"Bienstock, D., Michalka, A.: Cutting-planes for optimization of convex functions over nonconvex sets. SIAM J. Optim. 24(2), 643\u2013677 (2014)","journal-title":"SIAM J. Optim."},{"issue":"2","key":"33_CR13","doi-asserted-by":"publisher","first-page":"479","DOI":"10.1007\/s10107-008-0223-z","volume":"120","author":"S Burer","year":"2009","unstructured":"Burer, S.: On the copositive representation of binary and continuous nonconvex quadratic programs. Math. Program. 120(2), 479\u2013495 (2009). https:\/\/doi.org\/10.1007\/s10107-008-0223-z","journal-title":"Math. Program."},{"issue":"1\u20132","key":"33_CR14","doi-asserted-by":"publisher","first-page":"393","DOI":"10.1007\/s10107-016-1045-z","volume":"162","author":"S Burer","year":"2016","unstructured":"Burer, S., K\u0131l\u0131n\u00e7-Karzan, F.: How to convexify the intersection of a second order cone and a nonconvex quadratic. Math. Program. 162(1\u20132), 393\u2013429 (2016). https:\/\/doi.org\/10.1007\/s10107-016-1045-z","journal-title":"Math. Program."},{"key":"33_CR15","doi-asserted-by":"publisher","first-page":"595","DOI":"10.1007\/s101070050106","volume":"86","author":"S Ceria","year":"1999","unstructured":"Ceria, S., Soares, J.: Convex programming for disjunctive convex optimization. Math. Program. 86, 595\u2013614 (1999). https:\/\/doi.org\/10.1007\/s101070050106","journal-title":"Math. Program."},{"issue":"6","key":"33_CR16","doi-asserted-by":"publisher","first-page":"2211","DOI":"10.1002\/aic.14418","volume":"60","author":"A Cozad","year":"2014","unstructured":"Cozad, A., Sahinidis, N.V., Miller, D.C.: Learning surrogate models for simulation-based optimization. AIChE J. 60(6), 2211\u20132227 (2014)","journal-title":"AIChE J."},{"key":"33_CR17","doi-asserted-by":"publisher","first-page":"116","DOI":"10.1016\/j.compchemeng.2014.11.010","volume":"73","author":"A Cozad","year":"2015","unstructured":"Cozad, A., Sahinidis, N.V., Miller, D.C.: A combined first-principles and data-driven approach to model building. Comput. Chem. Eng. 73, 116\u2013127 (2015)","journal-title":"Comput. Chem. Eng."},{"issue":"3","key":"33_CR18","doi-asserted-by":"publisher","first-page":"208","DOI":"10.1016\/j.orl.2019.03.010","volume":"47","author":"H Dong","year":"2019","unstructured":"Dong, H.: On integer and MPCC representability of affine sparsity. Oper. Res. Lett. 47(3), 208\u2013212 (2019)","journal-title":"Oper. Res. Lett."},{"issue":"1\u20132","key":"33_CR19","doi-asserted-by":"publisher","first-page":"95","DOI":"10.1007\/s10107-018-1283-3","volume":"176","author":"H Dong","year":"2019","unstructured":"Dong, H., Ahn, M., Pang, J.-S.: Structural properties of affine sparsity constraints. Math. Program. 176(1\u20132), 95\u2013135 (2019). https:\/\/doi.org\/10.1007\/s10107-018-1283-3","journal-title":"Math. Program."},{"key":"33_CR20","unstructured":"Dong, H., Chen, K., Linderoth, J.: Regularization vs. relaxation: a conic optimization perspective of statistical variable selection. arXiv preprint arXiv:1510.06083 (2015)"},{"key":"33_CR21","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"169","DOI":"10.1007\/978-3-642-36694-9_15","volume-title":"Integer Programming and Combinatorial Optimization","author":"H Dong","year":"2013","unstructured":"Dong, H., Linderoth, J.: On valid inequalities for quadratic programming with continuous variables and binary indicators. In: Goemans, M., Correa, J. (eds.) IPCO 2013. LNCS, vol. 7801, pp. 169\u2013180. Springer, Heidelberg (2013). https:\/\/doi.org\/10.1007\/978-3-642-36694-9_15"},{"issue":"2","key":"33_CR22","doi-asserted-by":"publisher","first-page":"407","DOI":"10.1214\/009053604000000067","volume":"32","author":"B Efron","year":"2004","unstructured":"Efron, B., Hastie, T., Johnstone, I., Tibshirani, R.: Least angle regression. Ann. Stat. 32(2), 407\u2013499 (2004)","journal-title":"Ann. Stat."},{"issue":"456","key":"33_CR23","doi-asserted-by":"publisher","first-page":"1348","DOI":"10.1198\/016214501753382273","volume":"96","author":"J Fan","year":"2001","unstructured":"Fan, J., Li, R.: Variable selection via nonconcave penalized likelihood and its oracle properties. J. Am. Stat. Assoc. 96(456), 1348\u20131360 (2001)","journal-title":"J. Am. Stat. Assoc."},{"issue":"3","key":"33_CR24","doi-asserted-by":"publisher","first-page":"705","DOI":"10.1007\/s10589-015-9787-8","volume":"63","author":"A Frangioni","year":"2015","unstructured":"Frangioni, A., Furini, F., Gentile, C.: Approximated perspective relaxations: a project and lift approach. Comput. Optim. Appl. 63(3), 705\u2013735 (2015). https:\/\/doi.org\/10.1007\/s10589-015-9787-8","journal-title":"Comput. Optim. Appl."},{"key":"33_CR25","doi-asserted-by":"publisher","first-page":"225","DOI":"10.1007\/s10107-005-0594-3","volume":"106","author":"A Frangioni","year":"2006","unstructured":"Frangioni, A., Gentile, C.: Perspective cuts for a class of convex 0\u20131 mixed integer programs. Math. Program. 106, 225\u2013236 (2006). https:\/\/doi.org\/10.1007\/s10107-005-0594-3","journal-title":"Math. Program."},{"issue":"2","key":"33_CR26","doi-asserted-by":"publisher","first-page":"181","DOI":"10.1016\/j.orl.2006.03.008","volume":"35","author":"A Frangioni","year":"2007","unstructured":"Frangioni, A., Gentile, C.: SDP diagonalizations and perspective cuts for a class of nonseparable MIQP. Oper. Res. Lett. 35(2), 181\u2013185 (2007)","journal-title":"Oper. Res. Lett."},{"issue":"5","key":"33_CR27","doi-asserted-by":"publisher","first-page":"1225","DOI":"10.1287\/opre.1110.0930","volume":"59","author":"A Frangioni","year":"2011","unstructured":"Frangioni, A., Gentile, C., Grande, E., Pacifici, A.: Projected perspective reformulations with applications in design problems. Oper. Res. 59(5), 1225\u20131232 (2011)","journal-title":"Oper. Res."},{"key":"33_CR28","doi-asserted-by":"publisher","unstructured":"Frangioni, A., Gentile, C., Hungerford, J.: Decompositions of semidefinite matrices and the perspective reformulation of nonseparable quadratic programs. Math. Oper. Res. (2019). https:\/\/doi.org\/10.1287\/moor.2018.0969 . Article in Advance (October)","DOI":"10.1287\/moor.2018.0969"},{"key":"33_CR29","doi-asserted-by":"publisher","first-page":"183","DOI":"10.1007\/s10107-010-0360-z","volume":"124","author":"O G\u00fcnl\u00fck","year":"2010","unstructured":"G\u00fcnl\u00fck, O., Linderoth, J.: Perspective reformulations of mixed integer nonlinear programs with indicator variables. Math. Program. 124, 183\u2013205 (2010). https:\/\/doi.org\/10.1007\/s10107-010-0360-z","journal-title":"Math. Program."},{"key":"33_CR30","series-title":"Monographs on Statistics and Applied Probability","doi-asserted-by":"publisher","DOI":"10.1201\/b18401","volume-title":"Statistical Learning with Sparsity: The Lasso and Generalizations","author":"T Hastie","year":"2015","unstructured":"Hastie, T., Tibshirani, R., Wainwright, M.: Statistical Learning with Sparsity: The Lasso and Generalizations. Monographs on Statistics and Applied Probability, vol. 143. Chapman and Hall\/CRC, Boca Raton (2015)"},{"key":"33_CR31","unstructured":"Hazimeh, H., Mazumder, R.: Learning hierarchical interactions at scale: a convex optimization approach. arXiv preprint arXiv:1902.01542 (2019)"},{"issue":"2","key":"33_CR32","doi-asserted-by":"publisher","first-page":"537","DOI":"10.1007\/s10589-011-9424-0","volume":"52","author":"H Hijazi","year":"2012","unstructured":"Hijazi, H., Bonami, P., Cornu\u00e9jols, G., Ouorou, A.: Mixed-integer nonlinear programs featuring \u201con\/off\u201d constraints. Comput. Optim. Appl. 52(2), 537\u2013558 (2012). https:\/\/doi.org\/10.1007\/s10589-011-9424-0","journal-title":"Comput. Optim. Appl."},{"key":"33_CR33","unstructured":"Huang, J., Breheny, P., Ma, S.: A selective review of group selection in high-dimensional models. Stat. Sci.: Rev. J. Inst. Math. Stat. 27(4), 481\u2013499 (2012)"},{"key":"33_CR34","doi-asserted-by":"publisher","first-page":"32","DOI":"10.1016\/j.disopt.2016.04.008","volume":"24","author":"H Jeon","year":"2017","unstructured":"Jeon, H., Linderoth, J., Miller, A.: Quadratic cone cutting surfaces for quadratic programs with on-off constraints. Discrete Optim. 24, 32\u201350 (2017)","journal-title":"Discrete Optim."},{"key":"33_CR35","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"345","DOI":"10.1007\/978-3-319-07557-0_29","volume-title":"Integer Programming and Combinatorial Optimization","author":"F K\u0131l\u0131n\u00e7-Karzan","year":"2014","unstructured":"K\u0131l\u0131n\u00e7-Karzan, F., Y\u0131ld\u0131z, S.: Two-term disjunctions on the second-order cone. In: Lee, J., Vygen, J. (eds.) IPCO 2014. LNCS, vol. 8494, pp. 345\u2013356. Springer, Cham (2014). https:\/\/doi.org\/10.1007\/978-3-319-07557-0_29"},{"key":"33_CR36","unstructured":"Manzour, H., K\u00fc\u00e7\u00fckyavuz, S., Shojaie, A.: Integer programming for learning directed acyclic graphs from continuous data. arXiv preprint arXiv:1904.10574 (2019)"},{"key":"33_CR37","doi-asserted-by":"publisher","DOI":"10.1201\/9781420035933","volume-title":"Subset Selection in Regression","author":"A Miller","year":"2002","unstructured":"Miller, A.: Subset Selection in Regression. Chapman and Hall\/CRC, Boca Raton (2002). https:\/\/doi.org\/10.1201\/9781420035933"},{"issue":"1","key":"33_CR38","doi-asserted-by":"publisher","first-page":"575","DOI":"10.1007\/s10107-015-0866-5","volume":"155","author":"S Modaresi","year":"2015","unstructured":"Modaresi, S., K\u0131l\u0131n\u00e7, M.R., Vielma, J.P.: Intersection cuts for nonlinear integer programming: convexification techniques for structured sets. Math. Program. 155(1), 575\u2013611 (2015). https:\/\/doi.org\/10.1007\/s10107-015-0866-5","journal-title":"Math. Program."},{"issue":"2","key":"33_CR39","doi-asserted-by":"publisher","first-page":"227","DOI":"10.1137\/S0097539792240406","volume":"24","author":"BK Natarajan","year":"1995","unstructured":"Natarajan, B.K.: Sparse approximate solutions to linear systems. SIAM J. Comput. 24(2), 227\u2013234 (1995)","journal-title":"SIAM J. Comput."},{"issue":"1","key":"33_CR40","doi-asserted-by":"publisher","first-page":"61","DOI":"10.1007\/s10107-008-0226-9","volume":"121","author":"J-PP Richard","year":"2010","unstructured":"Richard, J.-P.P., Tawarmalani, M.: Lifting inequalities: a framework for generating strong cuts for nonlinear programs. Math. Program. 121(1), 61\u2013104 (2010). https:\/\/doi.org\/10.1007\/s10107-008-0226-9","journal-title":"Math. Program."},{"key":"33_CR41","doi-asserted-by":"crossref","first-page":"267","DOI":"10.1111\/j.2517-6161.1996.tb02080.x","volume":"58","author":"R Tibshirani","year":"1996","unstructured":"Tibshirani, R.: Regression shrinkage and selection via the lasso. J. Roy. Stat. Soc.: Ser. B (Methodol.) 58, 267\u2013288 (1996)","journal-title":"J. Roy. Stat. Soc.: Ser. B (Methodol.)"},{"issue":"1\u20132","key":"33_CR42","doi-asserted-by":"publisher","first-page":"21","DOI":"10.1007\/s10107-018-1258-4","volume":"177","author":"JP Vielma","year":"2019","unstructured":"Vielma, J.P.: Small and strong formulations for unions of convex sets from the Cayley embedding. Math. Program. 177(1\u20132), 21\u201353 (2019). https:\/\/doi.org\/10.1007\/s10107-018-1258-4","journal-title":"Math. Program."},{"key":"33_CR43","doi-asserted-by":"crossref","unstructured":"Wang, A.L., K\u0131l\u0131n\u00e7-Karzan, F.: The generalized trust region subproblem: solution complexity and convex hull results. arXiv preprint arXiv:1907.08843 (2019a)","DOI":"10.1007\/s10107-020-01560-8"},{"key":"33_CR44","unstructured":"Wang, A.L., K\u0131l\u0131n\u00e7-Karzan, F.: On the tightness of SDP relaxations of QCQPs. Optimization Online preprint (2019b). http:\/\/www.optimization-online.org\/DB_FILE\/2019\/11\/7487.pdf"},{"issue":"3","key":"33_CR45","doi-asserted-by":"publisher","first-page":"1531","DOI":"10.1137\/15M1012232","volume":"27","author":"B Wu","year":"2017","unstructured":"Wu, B., Sun, X., Li, D., Zheng, X.: Quadratic convex reformulations for semicontinuous quadratic programming. SIAM J. Optim. 27(3), 1531\u20131553 (2017)","journal-title":"SIAM J. Optim."},{"key":"33_CR46","unstructured":"Xie, W., Deng, X.: The CCP selector: scalable algorithms for sparse ridge regression from chance-constrained programming. arXiv preprint arXiv:1806.03756 (2018)"},{"key":"33_CR47","doi-asserted-by":"publisher","first-page":"894","DOI":"10.1214\/09-AOS729","volume":"38","author":"C-H Zhang","year":"2010","unstructured":"Zhang, C.-H.: Nearly unbiased variable selection under minimax concave penalty. Ann. Stat. 38, 894\u2013942 (2010)","journal-title":"Ann. Stat."},{"issue":"4","key":"33_CR48","doi-asserted-by":"publisher","first-page":"690","DOI":"10.1287\/ijoc.2014.0592","volume":"26","author":"X Zheng","year":"2014","unstructured":"Zheng, X., Sun, X., Li, D.: Improving the performance of MIQP solvers for quadratic programs with cardinality and minimum threshold constraints: a semidefinite program approach. INFORMS J. Comput. 26(4), 690\u2013703 (2014)","journal-title":"INFORMS J. Comput."}],"container-title":["Lecture Notes in Computer Science","Integer Programming and Combinatorial Optimization"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-030-45771-6_33","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,8,3]],"date-time":"2024-08-03T22:44:59Z","timestamp":1722725099000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/978-3-030-45771-6_33"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020]]},"ISBN":["9783030457709","9783030457716"],"references-count":48,"URL":"https:\/\/doi.org\/10.1007\/978-3-030-45771-6_33","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2020]]},"assertion":[{"value":"14 April 2020","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"IPCO","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Integer Programming and Combinatorial Optimization","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"London","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"United Kingdom","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2020","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"8 June 2020","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"10 June 2020","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"ipco2020","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/www.xixilogic.org\/events\/clar2020\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Single-blind","order":1,"name":"type","label":"Type","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"EasyChair","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"126","order":3,"name":"number_of_submissions_sent_for_review","label":"Number of Submissions Sent for Review","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"33","order":4,"name":"number_of_full_papers_accepted","label":"Number of Full Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"0","order":5,"name":"number_of_short_papers_accepted","label":"Number of Short Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"26% - The value is computed by the equation \"Number of Full Papers Accepted \/ Number of Submissions Sent for Review * 100\" and then rounded to a whole number.","order":6,"name":"acceptance_rate_of_full_papers","label":"Acceptance Rate of Full Papers","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"3","order":7,"name":"average_number_of_reviews_per_paper","label":"Average Number of Reviews per Paper","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"26","order":8,"name":"average_number_of_papers_per_reviewer","label":"Average Number of Papers per Reviewer","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"No","order":9,"name":"external_reviewers_involved","label":"External Reviewers Involved","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}}]}}