{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,15]],"date-time":"2025-11-15T07:28:25Z","timestamp":1763191705667,"version":"3.45.0"},"reference-count":34,"publisher":"IEEE","license":[{"start":{"date-parts":[[2025,6,30]],"date-time":"2025-06-30T00:00:00Z","timestamp":1751241600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2025,6,30]],"date-time":"2025-06-30T00:00:00Z","timestamp":1751241600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2025,6,30]]},"DOI":"10.1109\/ijcnn64981.2025.11227814","type":"proceedings-article","created":{"date-parts":[[2025,11,14]],"date-time":"2025-11-14T18:46:15Z","timestamp":1763145975000},"page":"1-8","source":"Crossref","is-referenced-by-count":0,"title":["A Deep Learning Approach to Shell and Tube Heat Exchangers Customization"],"prefix":"10.1109","author":[{"given":"Davide","family":"Rigoni","sequence":"first","affiliation":[{"name":"University of Padova,Padua,Italy"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Matteo","family":"Mirafiori","sequence":"additional","affiliation":[{"name":"terraXcube, Eurac Research,Bolzano,Italy"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Andrea","family":"Padovan","sequence":"additional","affiliation":[{"name":"Wieland Onda S.r.l,Mussolente,Italy"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Giuseppe","family":"Censi","sequence":"additional","affiliation":[{"name":"Wieland Onda S.r.l,Mussolente,Italy"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Alessandro","family":"Sperduti","sequence":"additional","affiliation":[{"name":"University of Padova,Padua,Italy"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"263","reference":[{"key":"ref1","first-page":"244","article-title":"On the optimization of deep networks: Implicit acceleration by overparameterization","volume-title":"ICML","author":"Arora","year":"2018"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1073\/pnas.1903070116"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1115\/1.1833366"},{"key":"ref4","first-page":"499","article-title":"Stability and generalization","volume":"2","author":"Bousquet","year":"2002","journal-title":"JMLR"},{"article-title":"Experimental and calculated heat transfer of a micro-fin shell-and-tube evaporator: R513a as drop-in replacement for r134a","volume-title":"Proc. 6th IIR Conf. Thermophys. Prop. Transfer Process. Refrig","author":"Censi","key":"ref5"},{"article-title":"R1234ze(e) as drop-in replacement for r134a in a micro-fin shell-and-tube evaporator: Experimental tests and calculation model","volume-title":"Int. Refrig. Air Cond. Conf","author":"Censi","key":"ref6"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2008.09.014"},{"key":"ref8","article-title":"Semi-flat minima and saddle points by embedding neural networks to overparameterization","volume":"32","author":"Fukumizu","year":"2019","journal-title":"NeurIPS"},{"key":"ref9","first-page":"13557","article-title":"Overparameterization from computational constraints","volume":"35","author":"Garg","year":"2022","journal-title":"NeurIPS"},{"key":"ref10","article-title":"Asymmetric valleys: Beyond sharp and flat local minima","volume":"32","author":"He","year":"2019","journal-title":"NeurIPS"},{"key":"ref11","first-page":"8635","article-title":"Sparse double descent: Where network pruning aggravates overfitting","volume-title":"ICML","author":"He","year":"2022"},{"key":"ref12","first-page":"16495","article-title":"Understanding square loss in training overparametrized neural network classifiers","volume":"35","author":"Hu","year":"2022","journal-title":"NeurIPS"},{"key":"ref13","first-page":"16563","article-title":"Provable generalization of overparameterized meta-learning trained with sgd","volume":"35","author":"Huang","year":"2022","journal-title":"NeurIPS"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.4314\/ejst.v8i2.5"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.32604\/fdmp.2022.021925"},{"key":"ref16","first-page":"16577","article-title":"When do flat minima optimizers work?","volume":"35","author":"Kaddour","year":"2022","journal-title":"NeurIPS"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1016\/j.patrec.2011.07.012"},{"key":"ref18","first-page":"13669","article-title":"Benefits of overparameterized convolutional residual networks: Function approximation under smoothness constraint","volume-title":"ICML","author":"Liu","year":"2022"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1007\/s10973-023-12265-3"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-24359-3"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1109\/TCYB.2014.2361857"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2023.126227"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1016\/j.enconman.2009.12.003"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1016\/j.applthermaleng.2010.03.001"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1080\/00401706.1996.10484565"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1017\/CBO9781107298019"},{"key":"ref27","first-page":"23479","article-title":"Generalization for multiclass classification with overparameterized linear models","volume":"35","author":"Subramanian","year":"2022","journal-title":"NeurIPS"},{"key":"ref28","article-title":"Principles of risk minimization for learning theory","volume":"4","author":"Vapnik","year":"1991","journal-title":"NeurIPS"},{"key":"ref29","first-page":"831","article-title":"Statistical learning theory","volume":"2","author":"Vapnik","year":"1998","journal-title":"John Wiley & Sons google schola"},{"key":"ref30","first-page":"22234","article-title":"On implicit bias in overparameterized bilevel optimization","volume-title":"ICML","author":"Vicol","year":"2022"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1007\/s11630-006-0257-6"},{"key":"ref32","first-page":"4680","article-title":"The alignment property of sgd noise and how it helps select flat minima: A stability analysis","volume":"35","author":"Wu","year":"2022","journal-title":"NeurIPS"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1016\/j.applthermaleng.2006.07.036"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.3390\/su13168824"}],"event":{"name":"2025 International Joint Conference on Neural Networks (IJCNN)","start":{"date-parts":[[2025,6,30]]},"location":"Rome, Italy","end":{"date-parts":[[2025,7,5]]}},"container-title":["2025 International Joint Conference on Neural Networks (IJCNN)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx8\/11227166\/11227148\/11227814.pdf?arnumber=11227814","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,11,15]],"date-time":"2025-11-15T07:25:51Z","timestamp":1763191551000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/11227814\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,6,30]]},"references-count":34,"URL":"https:\/\/doi.org\/10.1109\/ijcnn64981.2025.11227814","relation":{},"subject":[],"published":{"date-parts":[[2025,6,30]]}}}