{"id":"https://openalex.org/W4401863596","doi":"https://doi.org/10.1145/3637528.3671815","title":"NeuroCut: A Neural Approach for Robust Graph Partitioning","display_name":"NeuroCut: A Neural Approach for Robust Graph Partitioning","publication_year":2024,"publication_date":"2024-08-24","ids":{"openalex":"https://openalex.org/W4401863596","doi":"https://doi.org/10.1145/3637528.3671815"},"language":"en","primary_location":{"id":"doi:10.1145/3637528.3671815","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3637528.3671815","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5103069653","display_name":"Rishi Shah","orcid":"https://orcid.org/0009-0008-5842-5462"},"institutions":[{"id":"https://openalex.org/I68891433","display_name":"Indian Institute of Technology Delhi","ror":"https://ror.org/049tgcd06","country_code":"IN","type":"education","lineage":["https://openalex.org/I68891433"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Rishi Shah","raw_affiliation_strings":["Department of Computer Science and Engineering, IIT Delhi, New Delhi, India"],"raw_orcid":"https://orcid.org/0009-0008-5842-5462","affiliations":[{"raw_affiliation_string":"Department of Computer Science and Engineering, IIT Delhi, New Delhi, India","institution_ids":["https://openalex.org/I68891433"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5028535108","display_name":"Krishnanshu Jain","orcid":null},"institutions":[{"id":"https://openalex.org/I68891433","display_name":"Indian Institute of Technology Delhi","ror":"https://ror.org/049tgcd06","country_code":"IN","type":"education","lineage":["https://openalex.org/I68891433"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Krishnanshu Jain","raw_affiliation_strings":["Department of Computer Science and Engineering, IIT Delhi, New Delhi, India"],"raw_orcid":"https://orcid.org/0009-0003-5342-3920","affiliations":[{"raw_affiliation_string":"Department of Computer Science and Engineering, IIT Delhi, New Delhi, India","institution_ids":["https://openalex.org/I68891433"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5089895811","display_name":"Sahil Manchanda","orcid":"https://orcid.org/0000-0001-7437-9891"},"institutions":[{"id":"https://openalex.org/I68891433","display_name":"Indian Institute of Technology Delhi","ror":"https://ror.org/049tgcd06","country_code":"IN","type":"education","lineage":["https://openalex.org/I68891433"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Sahil Manchanda","raw_affiliation_strings":["Department of Computer Science and Engineering, IIT Delhi, New Delhi, India"],"raw_orcid":"https://orcid.org/0000-0001-7437-9891","affiliations":[{"raw_affiliation_string":"Department of Computer Science and Engineering, IIT Delhi, New Delhi, India","institution_ids":["https://openalex.org/I68891433"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5049055881","display_name":"Sourav Medya","orcid":"https://orcid.org/0000-0003-0996-2807"},"institutions":[{"id":"https://openalex.org/I39422238","display_name":"University of Illinois Chicago","ror":"https://ror.org/02mpq6x41","country_code":"US","type":"education","lineage":["https://openalex.org/I39422238"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Sourav Medya","raw_affiliation_strings":["University of Illinois at Chicago, Chicago, USA"],"raw_orcid":"https://orcid.org/0000-0003-0996-2807","affiliations":[{"raw_affiliation_string":"University of Illinois at Chicago, Chicago, USA","institution_ids":["https://openalex.org/I39422238"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5054697900","display_name":"Sayan Ranu","orcid":"https://orcid.org/0000-0003-4147-9372"},"institutions":[{"id":"https://openalex.org/I68891433","display_name":"Indian Institute of Technology Delhi","ror":"https://ror.org/049tgcd06","country_code":"IN","type":"education","lineage":["https://openalex.org/I68891433"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Sayan Ranu","raw_affiliation_strings":["Department of Computer Science and Engineering, IIT Delhi, New Delhi, India"],"raw_orcid":"https://orcid.org/0000-0003-4147-9372","affiliations":[{"raw_affiliation_string":"Department of Computer Science and Engineering, IIT Delhi, New Delhi, India","institution_ids":["https://openalex.org/I68891433"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"2584","last_page":"2595"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12292","display_name":"Graph Theory and Algorithms","score":0.9987000226974487,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T12292","display_name":"Graph Theory and Algorithms","score":0.9987000226974487,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10586","display_name":"Robotic Path Planning Algorithms","score":0.9944999814033508,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11522","display_name":"VLSI and FPGA Design Techniques","score":0.9896000027656555,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7186136245727539},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.4722404181957245},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.394431471824646},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.37444794178009033}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7186136245727539},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.4722404181957245},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.394431471824646},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.37444794178009033}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3637528.3671815","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3637528.3671815","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":28,"referenced_works":["https://openalex.org/W41554520","https://openalex.org/W1944814515","https://openalex.org/W2004951603","https://openalex.org/W2063491776","https://openalex.org/W2086254934","https://openalex.org/W2109220922","https://openalex.org/W2115049345","https://openalex.org/W2121947440","https://openalex.org/W2122466336","https://openalex.org/W2150062804","https://openalex.org/W2293888960","https://openalex.org/W2299467264","https://openalex.org/W2767404761","https://openalex.org/W2911826336","https://openalex.org/W3002481460","https://openalex.org/W3006206211","https://openalex.org/W3009669424","https://openalex.org/W3105358895","https://openalex.org/W3106318401","https://openalex.org/W3202610621","https://openalex.org/W4226070250","https://openalex.org/W4242608849","https://openalex.org/W4287749054","https://openalex.org/W4308148991","https://openalex.org/W4382462173","https://openalex.org/W4393156461","https://openalex.org/W4393161244","https://openalex.org/W6780230476"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2748952813","https://openalex.org/W2390279801","https://openalex.org/W2358668433","https://openalex.org/W4396701345","https://openalex.org/W2376932109","https://openalex.org/W2001405890","https://openalex.org/W4396696052","https://openalex.org/W2382290278","https://openalex.org/W4395014643"],"abstract_inverted_index":{"Graph":[0],"partitioning":[1,15,24,43,53,89,200],"aims":[2],"to":[3,22,28,47,168,206],"divide":[4],"a":[5,13,71,128,137,196],"graph":[6,23,138],"into":[7],"k":[8],"disjoint":[9],"subsets":[10],"while":[11],"optimizing":[12],"specific":[14],"objective.":[16],"The":[17],"majority":[18],"of":[19,74,87,99,106,172,199],"formulations":[20],"related":[21],"exhibit":[25],"NP-hardness":[26],"due":[27],"their":[29],"combinatorial":[30],"nature.":[31],"Conventional":[32],"methods,":[33],"like":[34],"approximation":[35],"algorithms":[36],"or":[37],"heuristics,":[38],"are":[39],"designed":[40],"for":[41,95],"distinct":[42,72],"objectives":[44],"and":[45,92,141,161,202],"fail":[46],"achieve":[48],"generalization":[49,194,205],"across":[50,195],"other":[51],"important":[52],"objectives.":[54],"Recently":[55],"machine":[56],"learning-based":[57,130],"methods":[58,69,84],"have":[59,70],"been":[60],"developed":[61],"that":[62,78,185],"learn":[63],"directly":[64],"from":[65,136],"data.":[66],"Further,":[67],"these":[68,83],"advantage":[73],"utilizing":[75],"node":[76,133],"features":[77],"carry":[79],"additional":[80],"information.":[81],"However,":[82],"assume":[85,103],"differentiability":[86],"target":[88],"objective":[90],"functions":[91],"cannot":[93],"generalize":[94],"an":[96],"unknown":[97],"number":[98,105,171],"partitions,":[100,191],"i.e.,":[101],"they":[102],"the":[104,158,162],"partitions":[107],"is":[108,175],"provided":[109,176],"in":[110,188],"advance.":[111],"In":[112],"this":[113],"study,":[114],"we":[115,156,183],"develop":[116],"NeuroCut":[117,144,166,186],"with":[118,152],"two":[119],"key":[120],"innovations":[121],"over":[122,132],"previous":[123],"methodologies.":[124],"First,":[125],"by":[126],"leveraging":[127],"reinforcement":[129],"framework":[131],"representations":[134],"derived":[135],"neural":[139],"network":[140],"positional":[142],"features,":[143],"can":[145],"accommodate":[146],"any":[147,169],"optimization":[148],"objective,":[149],"even":[150],"those":[151],"non-differentiable":[153],"functions.":[154],"Second,":[155],"decouple":[157],"parameter":[159],"space":[160],"partition":[163,208],"count":[164],"making":[165],"inductive":[167],"unseen":[170,207],"partition,":[173],"which":[174],"at":[177],"query":[178],"time.":[179],"Through":[180],"empirical":[181],"evaluation,":[182],"demonstrate":[184],"excels":[187],"identifying":[189],"high-quality":[190],"showcases":[192],"strong":[193,204],"wide":[197],"spectrum":[198],"objectives,":[201],"exhibits":[203],"count.":[209]},"counts_by_year":[{"year":2025,"cited_by_count":2}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}