{"id":"https://openalex.org/W4289655362","doi":"https://doi.org/10.1109/isit50566.2022.9834818","title":"Learning Maximum Margin Channel Decoders for Non-linear Gaussian Channels","display_name":"Learning Maximum Margin Channel Decoders for Non-linear Gaussian Channels","publication_year":2022,"publication_date":"2022-06-26","ids":{"openalex":"https://openalex.org/W4289655362","doi":"https://doi.org/10.1109/isit50566.2022.9834818"},"language":"en","primary_location":{"id":"doi:10.1109/isit50566.2022.9834818","is_oa":false,"landing_page_url":"https://doi.org/10.1109/isit50566.2022.9834818","pdf_url":null,"source":{"id":"https://openalex.org/S4363604560","display_name":"2022 IEEE International Symposium on Information Theory (ISIT)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 IEEE International Symposium on Information Theory (ISIT)","raw_type":"proceedings-article"},"type":"article","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/A5028077948","display_name":"Amit Tsvieli","orcid":"https://orcid.org/0000-0002-7805-6827"},"institutions":[{"id":"https://openalex.org/I174306211","display_name":"Technion \u2013 Israel Institute of Technology","ror":"https://ror.org/03qryx823","country_code":"IL","type":"education","lineage":["https://openalex.org/I174306211"]}],"countries":["IL"],"is_corresponding":true,"raw_author_name":"Amit Tsvieli","raw_affiliation_strings":["Technion - Israel Institute of Technology,The Viterbi Faculty of Electrical and Computer Engineering","The Viterbi Faculty of Electrical and Computer Engineering, Technion - Israel Institute of Technology"],"affiliations":[{"raw_affiliation_string":"Technion - Israel Institute of Technology,The Viterbi Faculty of Electrical and Computer Engineering","institution_ids":["https://openalex.org/I174306211"]},{"raw_affiliation_string":"The Viterbi Faculty of Electrical and Computer Engineering, Technion - Israel Institute of Technology","institution_ids":["https://openalex.org/I174306211"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5076051906","display_name":"Nir Weinberger","orcid":"https://orcid.org/0000-0001-6028-8892"},"institutions":[{"id":"https://openalex.org/I174306211","display_name":"Technion \u2013 Israel Institute of Technology","ror":"https://ror.org/03qryx823","country_code":"IL","type":"education","lineage":["https://openalex.org/I174306211"]}],"countries":["IL"],"is_corresponding":false,"raw_author_name":"Nir Weinberger","raw_affiliation_strings":["Technion - Israel Institute of Technology,The Viterbi Faculty of Electrical and Computer Engineering","The Viterbi Faculty of Electrical and Computer Engineering, Technion - Israel Institute of Technology"],"affiliations":[{"raw_affiliation_string":"Technion - Israel Institute of Technology,The Viterbi Faculty of Electrical and Computer Engineering","institution_ids":["https://openalex.org/I174306211"]},{"raw_affiliation_string":"The Viterbi Faculty of Electrical and Computer Engineering, Technion - Israel Institute of Technology","institution_ids":["https://openalex.org/I174306211"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5028077948"],"corresponding_institution_ids":["https://openalex.org/I174306211"],"apc_list":null,"apc_paid":null,"fwci":0.1046,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.27895267,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"2469","last_page":"2474"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12131","display_name":"Wireless Signal Modulation Classification","score":0.9998000264167786,"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/T12131","display_name":"Wireless Signal Modulation Classification","score":0.9998000264167786,"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/T10964","display_name":"Wireless Communication Security Techniques","score":0.9941999912261963,"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"}},{"id":"https://openalex.org/T12879","display_name":"Distributed Sensor Networks and Detection Algorithms","score":0.9922999739646912,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"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/hinge-loss","display_name":"Hinge loss","score":0.8288711905479431},{"id":"https://openalex.org/keywords/codebook","display_name":"Codebook","score":0.7161829471588135},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.5237645506858826},{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.4944748878479004},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.48010969161987305},{"id":"https://openalex.org/keywords/regularization","display_name":"Regularization (linguistics)","score":0.4772343933582306},{"id":"https://openalex.org/keywords/upper-and-lower-bounds","display_name":"Upper and lower bounds","score":0.43590784072875977},{"id":"https://openalex.org/keywords/stochastic-gradient-descent","display_name":"Stochastic gradient descent","score":0.43512290716171265},{"id":"https://openalex.org/keywords/gaussian-function","display_name":"Gaussian function","score":0.4280276894569397},{"id":"https://openalex.org/keywords/gradient-descent","display_name":"Gradient descent","score":0.4231328070163727},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.3732755184173584},{"id":"https://openalex.org/keywords/applied-mathematics","display_name":"Applied mathematics","score":0.3616560101509094},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.35698458552360535},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.2949468493461609},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.17462322115898132},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.1616312861442566},{"id":"https://openalex.org/keywords/mathematical-analysis","display_name":"Mathematical analysis","score":0.11521780490875244}],"concepts":[{"id":"https://openalex.org/C39891107","wikidata":"https://www.wikidata.org/wiki/Q5767098","display_name":"Hinge loss","level":3,"score":0.8288711905479431},{"id":"https://openalex.org/C127759330","wikidata":"https://www.wikidata.org/wiki/Q637416","display_name":"Codebook","level":2,"score":0.7161829471588135},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.5237645506858826},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.4944748878479004},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.48010969161987305},{"id":"https://openalex.org/C2776135515","wikidata":"https://www.wikidata.org/wiki/Q17143721","display_name":"Regularization (linguistics)","level":2,"score":0.4772343933582306},{"id":"https://openalex.org/C77553402","wikidata":"https://www.wikidata.org/wiki/Q13222579","display_name":"Upper and lower bounds","level":2,"score":0.43590784072875977},{"id":"https://openalex.org/C206688291","wikidata":"https://www.wikidata.org/wiki/Q7617819","display_name":"Stochastic gradient descent","level":3,"score":0.43512290716171265},{"id":"https://openalex.org/C7218915","wikidata":"https://www.wikidata.org/wiki/Q1054475","display_name":"Gaussian function","level":3,"score":0.4280276894569397},{"id":"https://openalex.org/C153258448","wikidata":"https://www.wikidata.org/wiki/Q1199743","display_name":"Gradient descent","level":3,"score":0.4231328070163727},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.3732755184173584},{"id":"https://openalex.org/C28826006","wikidata":"https://www.wikidata.org/wiki/Q33521","display_name":"Applied mathematics","level":1,"score":0.3616560101509094},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.35698458552360535},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.2949468493461609},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.17462322115898132},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.1616312861442566},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.11521780490875244},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/isit50566.2022.9834818","is_oa":false,"landing_page_url":"https://doi.org/10.1109/isit50566.2022.9834818","pdf_url":null,"source":{"id":"https://openalex.org/S4363604560","display_name":"2022 IEEE International Symposium on Information Theory (ISIT)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 IEEE International Symposium on Information Theory (ISIT)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":43,"referenced_works":["https://openalex.org/W1602492977","https://openalex.org/W1964077759","https://openalex.org/W2030811966","https://openalex.org/W2077782702","https://openalex.org/W2091475238","https://openalex.org/W2111187851","https://openalex.org/W2131680270","https://openalex.org/W2142623206","https://openalex.org/W2158234251","https://openalex.org/W2161065057","https://openalex.org/W2400159820","https://openalex.org/W2546945975","https://openalex.org/W2584943905","https://openalex.org/W2666368276","https://openalex.org/W2734408173","https://openalex.org/W2922456039","https://openalex.org/W2950213416","https://openalex.org/W2964231443","https://openalex.org/W2970898848","https://openalex.org/W2970958841","https://openalex.org/W2975585678","https://openalex.org/W2976077638","https://openalex.org/W2976123094","https://openalex.org/W2976843127","https://openalex.org/W2982142226","https://openalex.org/W2982169171","https://openalex.org/W3081045327","https://openalex.org/W3105371711","https://openalex.org/W3126945602","https://openalex.org/W3162220519","https://openalex.org/W3196968947","https://openalex.org/W3216382785","https://openalex.org/W4233622607","https://openalex.org/W4236362309","https://openalex.org/W4319778066","https://openalex.org/W6747916894","https://openalex.org/W6760287093","https://openalex.org/W6769737164","https://openalex.org/W6770020022","https://openalex.org/W6795027320","https://openalex.org/W6804018198","https://openalex.org/W6810848062","https://openalex.org/W6891330591"],"related_works":["https://openalex.org/W3197169288","https://openalex.org/W4206903459","https://openalex.org/W2754816816","https://openalex.org/W4366280654","https://openalex.org/W3160167280","https://openalex.org/W4231621013","https://openalex.org/W4362706668","https://openalex.org/W3008318776","https://openalex.org/W2041416246","https://openalex.org/W3020853991"],"abstract_inverted_index":{"The":[0,17,53,184],"problem":[1,69,165],"of":[2,29,34,55,59,107,119,150,180,186],"learning":[3],"a":[4,22,26,42,45,50,65,71,76,117,124,130,148,178],"channel":[5,14],"decoder":[6,48,61],"for":[7,44,91,98,104,139,159],"an":[8,169,193],"unknown":[9],"non-linear":[10],"white":[11],"Gaussian":[12],"noise":[13],"is":[15,19,38,62,80,83,102,123,137,166,173,190],"considered.":[16],"learner":[18],"provided":[20,103,138],"with":[21,49,70],"fixed":[23],"codebook":[24],"and":[25,37,75,112,143,168],"dataset":[27],"comprised":[28],"n":[30,152],"independent":[31],"input-output":[32],"samples":[33],"the":[35,57,60,86,105,108,140,161,187],"channel,":[36],"required":[39],"to":[40,114,145],"select":[41],"matrix":[43],"nearest":[46],"neighbor":[47],"linear":[51],"kernel.":[52],"objective":[54],"maximizing":[56],"margin":[58],"addressed.":[63],"Accordingly,":[64],"regularized":[66,109,162],"loss":[67,78,101,110,163],"minimization":[68,164],"codebook-related":[72],"regularization":[73,125],"term":[74],"hinge-like":[77],"function":[79],"developed,":[81],"which":[82,175],"inspired":[84],"by":[85,192],"support":[87],"vector":[88],"machine":[89],"paradigm":[90],"classification":[92],"problems.":[93],"Expected":[94],"generalization":[95,134],"error":[96,135,171],"bound":[97,136,172],"that":[99],"hinge":[100],"solution":[106],"minimization,":[111],"shown":[113,144],"scale":[115,146],"at":[116,147,177],"rate":[118,149,179],"O(1/(\u03bbn)),":[120],"where":[121],"\u03bb":[122],"tradeoff":[126],"parameter.":[127],"In":[128],"addition,":[129],"high":[131],"probability":[132],"uniform":[133],"hypothesis":[141],"class,":[142],"$O(1/\\sqrt":[151],")$.":[153],"A":[154],"stochastic":[155],"sub-gradient":[156],"descent":[157],"algorithm":[158,189],"solving":[160],"proposed,":[167],"optimization":[170],"stated,":[174],"scales":[176],"$\\tilde":[181],"O(1/(\\lambda":[182],"T))$.":[183],"performance":[185],"this":[188],"demonstrated":[191],"example.":[194]},"counts_by_year":[{"year":2023,"cited_by_count":1}],"updated_date":"2026-03-25T13:04:00.132906","created_date":"2025-10-10T00:00:00"}