{"id":"https://openalex.org/W7165680951","doi":"https://doi.org/10.1145/3806789.3810252","title":"Dimensional Peeking for Low-Variance Gradients in Zeroth-Order Discrete Optimization via Simulation","display_name":"Dimensional Peeking for Low-Variance Gradients in Zeroth-Order Discrete Optimization via Simulation","publication_year":2026,"publication_date":"2026-06-23","ids":{"openalex":"https://openalex.org/W7165680951","doi":"https://doi.org/10.1145/3806789.3810252"},"language":null,"primary_location":{"id":"doi:10.1145/3806789.3810252","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3806789.3810252","pdf_url":null,"source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 40th ACM SIGSIM International Conference on Principles of Advanced Discrete Simulation","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1145/3806789.3810252","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5042423448","display_name":"Philipp Andelfinger","orcid":"https://orcid.org/0000-0002-0211-7136"},"institutions":[{"id":"https://openalex.org/I172675005","display_name":"Nanyang Technological University","ror":"https://ror.org/02e7b5302","country_code":"SG","type":"education","lineage":["https://openalex.org/I172675005"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"Philipp Andelfinger","raw_affiliation_strings":["Nanyang Technological University, Singapore, Singapore"],"raw_orcid":"https://orcid.org/0000-0002-0211-7136","affiliations":[{"raw_affiliation_string":"Nanyang Technological University, Singapore, Singapore","institution_ids":["https://openalex.org/I172675005"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5103068388","display_name":"Wentong Cai","orcid":"https://orcid.org/0000-0002-0782-1341"},"institutions":[{"id":"https://openalex.org/I172675005","display_name":"Nanyang Technological University","ror":"https://ror.org/02e7b5302","country_code":"SG","type":"education","lineage":["https://openalex.org/I172675005"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"Wentong Cai","raw_affiliation_strings":["Nanyang Technological University, Singapore, Singapore"],"raw_orcid":"https://orcid.org/0000-0002-0782-1341","affiliations":[{"raw_affiliation_string":"Nanyang Technological University, Singapore, Singapore","institution_ids":["https://openalex.org/I172675005"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I172675005"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.72630067,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"78","last_page":"87"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11612","display_name":"Stochastic Gradient Optimization Techniques","score":0.8804000020027161,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/T11612","display_name":"Stochastic Gradient Optimization Techniques","score":0.8804000020027161,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/T11195","display_name":"Simulation Techniques and Applications","score":0.021400000900030136,"subfield":{"id":"https://openalex.org/subfields/1803","display_name":"Management Science and Operations Research"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T10963","display_name":"Advanced Optimization Algorithms Research","score":0.021199999377131462,"subfield":{"id":"https://openalex.org/subfields/2612","display_name":"Numerical Analysis"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/variance-reduction","display_name":"Variance reduction","score":0.7052000164985657},{"id":"https://openalex.org/keywords/estimator","display_name":"Estimator","score":0.7045999765396118},{"id":"https://openalex.org/keywords/optimization-problem","display_name":"Optimization problem","score":0.5439000129699707},{"id":"https://openalex.org/keywords/granularity","display_name":"Granularity","score":0.5185999870300293},{"id":"https://openalex.org/keywords/variance","display_name":"Variance (accounting)","score":0.5138000249862671},{"id":"https://openalex.org/keywords/sampling","display_name":"Sampling (signal processing)","score":0.5105999708175659},{"id":"https://openalex.org/keywords/random-optimization","display_name":"Random optimization","score":0.4878999888896942},{"id":"https://openalex.org/keywords/discrete-optimization","display_name":"Discrete optimization","score":0.44269999861717224}],"concepts":[{"id":"https://openalex.org/C62644790","wikidata":"https://www.wikidata.org/wiki/Q3454689","display_name":"Variance reduction","level":3,"score":0.7052000164985657},{"id":"https://openalex.org/C185429906","wikidata":"https://www.wikidata.org/wiki/Q1130160","display_name":"Estimator","level":2,"score":0.7045999765396118},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.633400022983551},{"id":"https://openalex.org/C137836250","wikidata":"https://www.wikidata.org/wiki/Q984063","display_name":"Optimization problem","level":2,"score":0.5439000129699707},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.5315999984741211},{"id":"https://openalex.org/C177774035","wikidata":"https://www.wikidata.org/wiki/Q1246948","display_name":"Granularity","level":2,"score":0.5185999870300293},{"id":"https://openalex.org/C196083921","wikidata":"https://www.wikidata.org/wiki/Q7915758","display_name":"Variance (accounting)","level":2,"score":0.5138000249862671},{"id":"https://openalex.org/C140779682","wikidata":"https://www.wikidata.org/wiki/Q210868","display_name":"Sampling (signal processing)","level":3,"score":0.5105999708175659},{"id":"https://openalex.org/C109578324","wikidata":"https://www.wikidata.org/wiki/Q3354463","display_name":"Random optimization","level":5,"score":0.4878999888896942},{"id":"https://openalex.org/C145671259","wikidata":"https://www.wikidata.org/wiki/Q1493786","display_name":"Discrete optimization","level":3,"score":0.44269999861717224},{"id":"https://openalex.org/C14036430","wikidata":"https://www.wikidata.org/wiki/Q3736076","display_name":"Function (biology)","level":2,"score":0.41909998655319214},{"id":"https://openalex.org/C57691317","wikidata":"https://www.wikidata.org/wiki/Q1289248","display_name":"Scalar (mathematics)","level":2,"score":0.41530001163482666},{"id":"https://openalex.org/C2780009758","wikidata":"https://www.wikidata.org/wiki/Q6804172","display_name":"Measure (data warehouse)","level":2,"score":0.36660000681877136},{"id":"https://openalex.org/C164752517","wikidata":"https://www.wikidata.org/wiki/Q5570875","display_name":"Global optimization","level":2,"score":0.36550000309944153},{"id":"https://openalex.org/C52740198","wikidata":"https://www.wikidata.org/wiki/Q1539564","display_name":"Importance sampling","level":3,"score":0.35350000858306885},{"id":"https://openalex.org/C28826006","wikidata":"https://www.wikidata.org/wiki/Q33521","display_name":"Applied mathematics","level":1,"score":0.34709998965263367},{"id":"https://openalex.org/C111335779","wikidata":"https://www.wikidata.org/wiki/Q3454686","display_name":"Reduction (mathematics)","level":2,"score":0.33489999175071716},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.32359999418258667},{"id":"https://openalex.org/C194387892","wikidata":"https://www.wikidata.org/wiki/Q1747770","display_name":"Stochastic optimization","level":2,"score":0.320499986410141},{"id":"https://openalex.org/C38349280","wikidata":"https://www.wikidata.org/wiki/Q1434290","display_name":"Flow (mathematics)","level":2,"score":0.3100999891757965},{"id":"https://openalex.org/C2987595161","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Optimization algorithm","level":2,"score":0.30640000104904175},{"id":"https://openalex.org/C55689738","wikidata":"https://www.wikidata.org/wiki/Q15963867","display_name":"Discrete time and continuous time","level":2,"score":0.274399995803833},{"id":"https://openalex.org/C115680565","wikidata":"https://www.wikidata.org/wiki/Q5977448","display_name":"Gradient method","level":2,"score":0.2736000120639801},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.2694999873638153},{"id":"https://openalex.org/C2775924081","wikidata":"https://www.wikidata.org/wiki/Q55608371","display_name":"Control (management)","level":2,"score":0.2563999891281128}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3806789.3810252","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3806789.3810252","pdf_url":null,"source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 40th ACM SIGSIM International Conference on Principles of Advanced Discrete Simulation","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1145/3806789.3810252","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3806789.3810252","pdf_url":null,"source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 40th ACM SIGSIM International Conference on Principles of Advanced Discrete Simulation","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":29,"referenced_works":["https://openalex.org/W600148761","https://openalex.org/W1498436455","https://openalex.org/W1977417413","https://openalex.org/W1979382551","https://openalex.org/W2052919414","https://openalex.org/W2059577760","https://openalex.org/W2124289529","https://openalex.org/W2149479912","https://openalex.org/W2591096648","https://openalex.org/W2783515600","https://openalex.org/W2901943374","https://openalex.org/W2941034199","https://openalex.org/W2945991855","https://openalex.org/W2963470657","https://openalex.org/W2963480953","https://openalex.org/W3136297071","https://openalex.org/W3157244600","https://openalex.org/W3181693521","https://openalex.org/W4241811150","https://openalex.org/W4292403327","https://openalex.org/W4293239110","https://openalex.org/W4303185468","https://openalex.org/W4323669212","https://openalex.org/W4372352735","https://openalex.org/W4389664989","https://openalex.org/W4400097693","https://openalex.org/W4400447170","https://openalex.org/W4411515846","https://openalex.org/W7133191466"],"related_works":[],"abstract_inverted_index":{"Gradient-based":[0],"optimization":[1,58,137,143,158],"methods":[2],"are":[3,132],"commonly":[4],"used":[5],"to":[6,39,69,115,130,146],"identify":[7],"local":[8],"optima":[9],"in":[10,56],"high-dimensional":[11,140],"spaces.":[12],"When":[13],"derivatives":[14],"cannot":[15],"be":[16],"evaluated":[17],"directly,":[18],"stochastic":[19],"estimators":[20],"can":[21,37],"provide":[22],"approximate":[23],"gradients.":[24],"However,":[25],"these":[26],"estimators\u2019":[27],"perturbation-based":[28],"sampling":[29,64],"of":[30,71,128,156],"the":[31,63,75,82,98,154],"objective":[32],"function":[33],"introduces":[34],"variance":[35,50],"that":[36,73,97,150],"lead":[38],"slow":[40],"convergence.":[41],"In":[42],"this":[43],"paper,":[44],"we":[45,80],"present":[46,106],"dimensional":[47,119,151],"peeking,":[48],"a":[49,110],"reduction":[51],"method":[52,99],"for":[53,134,159],"gradient":[54,94],"estimation":[55],"discrete":[57,160],"via":[59,109],"simulation.":[60],"By":[61],"lifting":[62],"granularity":[65],"from":[66,90],"scalar":[67],"values":[68,72],"classes":[70],"follow":[74],"same":[76],"control":[77],"flow":[78],"path,":[79],"increase":[81],"information":[83],"gathered":[84],"per":[85],"simulation":[86],"evaluation.":[87],"Our":[88],"derivation":[89],"an":[91,107],"established":[92],"smoothed":[93],"estimator":[95],"shows":[96,149],"does":[100],"not":[101],"introduce":[102],"any":[103],"bias.":[104],"We":[105],"implementation":[108],"custom":[111],"numerical":[112],"data":[113],"type":[114],"transparently":[116],"carry":[117],"out":[118],"peeking":[120,152],"over":[121],"C++":[122],"programs.":[123],"Variance":[124],"reductions":[125],"by":[126],"factors":[127],"up":[129],"7.9":[131],"observed":[133],"three":[135,147],"simulation-based":[136],"problems":[138],"with":[139],"input.":[141],"The":[142],"progress":[144],"compared":[145],"meta-heuristics":[148],"increases":[153],"competitiveness":[155],"zeroth-order":[157],"and":[161],"non-convex":[162],"simulations.":[163]},"counts_by_year":[],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2026-06-24T00:00:00"}