{"id":"https://openalex.org/W4415125390","doi":"https://doi.org/10.1109/icnp65844.2025.11192398","title":"OddEEC: A New Sketch Technique for Error Estimating Coding","display_name":"OddEEC: A New Sketch Technique for Error Estimating Coding","publication_year":2025,"publication_date":"2025-09-22","ids":{"openalex":"https://openalex.org/W4415125390","doi":"https://doi.org/10.1109/icnp65844.2025.11192398"},"language":"en","primary_location":{"id":"doi:10.1109/icnp65844.2025.11192398","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icnp65844.2025.11192398","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE 33rd International Conference on Network Protocols (ICNP)","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/A5012792241","display_name":"Huayi Wang","orcid":"https://orcid.org/0000-0001-6274-3844"},"institutions":[{"id":"https://openalex.org/I130701444","display_name":"Georgia Institute of Technology","ror":"https://ror.org/01zkghx44","country_code":"US","type":"education","lineage":["https://openalex.org/I130701444"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Huayi Wang","raw_affiliation_strings":["Georgia Institute of Technology,Atlanta,GA,USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Georgia Institute of Technology,Atlanta,GA,USA","institution_ids":["https://openalex.org/I130701444"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5013337954","display_name":"Jingfan Meng","orcid":null},"institutions":[{"id":"https://openalex.org/I130701444","display_name":"Georgia Institute of Technology","ror":"https://ror.org/01zkghx44","country_code":"US","type":"education","lineage":["https://openalex.org/I130701444"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jingfan Meng","raw_affiliation_strings":["Georgia Institute of Technology,Atlanta,GA,USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Georgia Institute of Technology,Atlanta,GA,USA","institution_ids":["https://openalex.org/I130701444"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5025728584","display_name":"Jun Xu","orcid":"https://orcid.org/0000-0002-0046-8119"},"institutions":[{"id":"https://openalex.org/I130701444","display_name":"Georgia Institute of Technology","ror":"https://ror.org/01zkghx44","country_code":"US","type":"education","lineage":["https://openalex.org/I130701444"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jun Xu","raw_affiliation_strings":["Georgia Institute of Technology,Atlanta,GA,USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Georgia Institute of Technology,Atlanta,GA,USA","institution_ids":["https://openalex.org/I130701444"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I130701444"],"apc_list":null,"apc_paid":null,"fwci":2.5254,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.88957055,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"11"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11697","display_name":"Numerical Methods and Algorithms","score":0.9810000061988831,"subfield":{"id":"https://openalex.org/subfields/1703","display_name":"Computational Theory and Mathematics"},"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/T11697","display_name":"Numerical Methods and Algorithms","score":0.9810000061988831,"subfield":{"id":"https://openalex.org/subfields/1703","display_name":"Computational Theory and Mathematics"},"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/T11034","display_name":"Digital Filter Design and Implementation","score":0.9395999908447266,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/sketch","display_name":"Sketch","score":0.7599999904632568},{"id":"https://openalex.org/keywords/decoding-methods","display_name":"Decoding methods","score":0.5849999785423279},{"id":"https://openalex.org/keywords/coding","display_name":"Coding (social sciences)","score":0.5236999988555908},{"id":"https://openalex.org/keywords/error-detection-and-correction","display_name":"Error detection and correction","score":0.44929999113082886},{"id":"https://openalex.org/keywords/network-packet","display_name":"Network packet","score":0.4413999915122986},{"id":"https://openalex.org/keywords/maximum-likelihood","display_name":"Maximum likelihood","score":0.3736000061035156},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.3589000105857849},{"id":"https://openalex.org/keywords/encoder","display_name":"Encoder","score":0.3319999873638153},{"id":"https://openalex.org/keywords/estimation-theory","display_name":"Estimation theory","score":0.3158000111579895}],"concepts":[{"id":"https://openalex.org/C2779231336","wikidata":"https://www.wikidata.org/wiki/Q7534724","display_name":"Sketch","level":2,"score":0.7599999904632568},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.679099977016449},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.6019999980926514},{"id":"https://openalex.org/C57273362","wikidata":"https://www.wikidata.org/wiki/Q576722","display_name":"Decoding methods","level":2,"score":0.5849999785423279},{"id":"https://openalex.org/C179518139","wikidata":"https://www.wikidata.org/wiki/Q5140297","display_name":"Coding (social sciences)","level":2,"score":0.5236999988555908},{"id":"https://openalex.org/C103088060","wikidata":"https://www.wikidata.org/wiki/Q1062839","display_name":"Error detection and correction","level":2,"score":0.44929999113082886},{"id":"https://openalex.org/C158379750","wikidata":"https://www.wikidata.org/wiki/Q214111","display_name":"Network packet","level":2,"score":0.4413999915122986},{"id":"https://openalex.org/C49781872","wikidata":"https://www.wikidata.org/wiki/Q1045555","display_name":"Maximum likelihood","level":2,"score":0.3736000061035156},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.3589000105857849},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3474000096321106},{"id":"https://openalex.org/C118505674","wikidata":"https://www.wikidata.org/wiki/Q42586063","display_name":"Encoder","level":2,"score":0.3319999873638153},{"id":"https://openalex.org/C167928553","wikidata":"https://www.wikidata.org/wiki/Q1376021","display_name":"Estimation theory","level":2,"score":0.3158000111579895},{"id":"https://openalex.org/C56296756","wikidata":"https://www.wikidata.org/wiki/Q840922","display_name":"Bit error rate","level":3,"score":0.3093999922275543},{"id":"https://openalex.org/C76862118","wikidata":"https://www.wikidata.org/wiki/Q1105671","display_name":"Coding gain","level":3,"score":0.30489999055862427},{"id":"https://openalex.org/C165473641","wikidata":"https://www.wikidata.org/wiki/Q3306280","display_name":"Sampling error","level":3,"score":0.29750001430511475},{"id":"https://openalex.org/C60603091","wikidata":"https://www.wikidata.org/wiki/Q2981616","display_name":"Variable-length code","level":3,"score":0.2847999930381775},{"id":"https://openalex.org/C9357733","wikidata":"https://www.wikidata.org/wiki/Q6878417","display_name":"Missing data","level":2,"score":0.2818000018596649},{"id":"https://openalex.org/C167085575","wikidata":"https://www.wikidata.org/wiki/Q6803654","display_name":"Mean squared prediction error","level":2,"score":0.2802000045776367},{"id":"https://openalex.org/C19619285","wikidata":"https://www.wikidata.org/wiki/Q196372","display_name":"Observational error","level":2,"score":0.2727000117301941},{"id":"https://openalex.org/C140779682","wikidata":"https://www.wikidata.org/wiki/Q210868","display_name":"Sampling (signal processing)","level":3,"score":0.26409998536109924},{"id":"https://openalex.org/C78548338","wikidata":"https://www.wikidata.org/wiki/Q2493","display_name":"Data compression","level":2,"score":0.25690001249313354},{"id":"https://openalex.org/C761482","wikidata":"https://www.wikidata.org/wiki/Q118093","display_name":"Transmission (telecommunications)","level":2,"score":0.25679999589920044},{"id":"https://openalex.org/C139945424","wikidata":"https://www.wikidata.org/wiki/Q1940696","display_name":"Mean squared error","level":2,"score":0.2556000053882599},{"id":"https://openalex.org/C3018824978","wikidata":"https://www.wikidata.org/wiki/Q2894891","display_name":"Error analysis","level":2,"score":0.25}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icnp65844.2025.11192398","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icnp65844.2025.11192398","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE 33rd International Conference on Network Protocols (ICNP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":26,"referenced_works":["https://openalex.org/W1973613668","https://openalex.org/W1991800036","https://openalex.org/W2008365755","https://openalex.org/W2053376180","https://openalex.org/W2060170830","https://openalex.org/W2099111195","https://openalex.org/W2126679271","https://openalex.org/W2160872168","https://openalex.org/W2168476654","https://openalex.org/W2487095677","https://openalex.org/W2558630945","https://openalex.org/W2595926085","https://openalex.org/W2761099162","https://openalex.org/W2834288129","https://openalex.org/W2914123175","https://openalex.org/W2963924281","https://openalex.org/W2967106834","https://openalex.org/W2969882361","https://openalex.org/W3003688116","https://openalex.org/W3012305473","https://openalex.org/W3138585045","https://openalex.org/W3192352544","https://openalex.org/W4376481159","https://openalex.org/W4386396862","https://openalex.org/W4400909672","https://openalex.org/W4415125390"],"related_works":[],"abstract_inverted_index":{"Error":[0],"estimating":[1,9],"coding":[2],"(EEC)":[3],"is":[4,32],"a":[5,27,33,37],"standard":[6],"technique":[7,40,54],"for":[8],"the":[10],"number":[11],"of":[12,36],"bit":[13,52],"errors":[14],"during":[15],"packet":[16],"transmission":[17],"over":[18],"wireless":[19],"networks.":[20],"In":[21],"this":[22],"paper,":[23],"we":[24],"propose":[25],"OddEEC,":[26],"novel":[28],"EEC":[29],"scheme.":[30],"OddEEC":[31,63],"nontrivial":[34],"adaptation":[35],"data":[38],"sketching":[39],"named":[41],"Odd":[42],"Sketch":[43],"to":[44],"EEC,":[45],"addressing":[46],"new":[47],"challenges":[48],"therein":[49],"by":[50],"its":[51],"sampling":[53],"and":[55,75],"maximum":[56],"likelihood":[57],"estimator.":[58],"Our":[59],"experiments":[60],"show":[61],"that":[62],"overall":[64],"achieves":[65],"comparable":[66],"estimation":[67],"accuracy":[68],"as":[69,73],"competing":[70],"schemes":[71],"such":[72],"gEEC":[74],"mEEC,":[76],"with":[77],"much":[78],"smaller":[79],"decoding":[80],"complexity.":[81]},"counts_by_year":[{"year":2025,"cited_by_count":1}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-14T00:00:00"}
