{"id":"https://openalex.org/W2752432813","doi":"https://doi.org/10.1109/tnnls.2019.2934225","title":"Optimizing for Measure of Performance in Max-Margin Parsing","display_name":"Optimizing for Measure of Performance in Max-Margin Parsing","publication_year":2019,"publication_date":"2019-01-01","ids":{"openalex":"https://openalex.org/W2752432813","doi":"https://doi.org/10.1109/tnnls.2019.2934225","mag":"2752432813","pmid":"https://pubmed.ncbi.nlm.nih.gov/31494564"},"language":"en","primary_location":{"id":"doi:10.1109/tnnls.2019.2934225","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tnnls.2019.2934225","pdf_url":null,"source":{"id":"https://openalex.org/S4210175523","display_name":"IEEE Transactions on Neural Networks and Learning Systems","issn_l":"2162-237X","issn":["2162-237X","2162-2388"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Neural Networks and Learning Systems","raw_type":"journal-article"},"type":"article","indexed_in":["arxiv","crossref","datacite","pubmed"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/1709.01562","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5102929251","display_name":"Alexander Bauer","orcid":"https://orcid.org/0000-0003-0443-3164"},"institutions":[{"id":"https://openalex.org/I4577782","display_name":"Technische Universit\u00e4t Berlin","ror":"https://ror.org/03v4gjf40","country_code":"DE","type":"education","lineage":["https://openalex.org/I4577782"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Alexander Bauer","raw_affiliation_strings":["Machine Learning Group, Technische Universit\u00e4t Berlin, Berlin, Germany","Machine Learning Group, Technische Universit\u00e4t Berlin Berlin, Germany"],"raw_orcid":"https://orcid.org/0000-0003-0443-3164","affiliations":[{"raw_affiliation_string":"Machine Learning Group, Technische Universit\u00e4t Berlin, Berlin, Germany","institution_ids":["https://openalex.org/I4577782"]},{"raw_affiliation_string":"Machine Learning Group, Technische Universit\u00e4t Berlin Berlin, Germany","institution_ids":["https://openalex.org/I4577782"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5034738514","display_name":"Shinichi Nakajima","orcid":"https://orcid.org/0000-0003-3970-4569"},"institutions":[{"id":"https://openalex.org/I4210126580","display_name":"RIKEN Center for Advanced Intelligence Project","ror":"https://ror.org/03ckxwf91","country_code":"JP","type":"facility","lineage":["https://openalex.org/I4210110652","https://openalex.org/I4210126580"]},{"id":"https://openalex.org/I4577782","display_name":"Technische Universit\u00e4t Berlin","ror":"https://ror.org/03v4gjf40","country_code":"DE","type":"education","lineage":["https://openalex.org/I4577782"]}],"countries":["DE","JP"],"is_corresponding":false,"raw_author_name":"Shinichi Nakajima","raw_affiliation_strings":["Berlin Big Data Center, Machine Learning Group, Technische Universit\u00e4t Berlin, Berlin, Germany","RIKEN AIP Center, Tokyo, Japan","[Berlin Big Data Center, Machine Learning Group, Technische Universit\u00e4t Berlin, Berlin, Germany]"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Berlin Big Data Center, Machine Learning Group, Technische Universit\u00e4t Berlin, Berlin, Germany","institution_ids":["https://openalex.org/I4577782"]},{"raw_affiliation_string":"RIKEN AIP Center, Tokyo, Japan","institution_ids":["https://openalex.org/I4210126580"]},{"raw_affiliation_string":"[Berlin Big Data Center, Machine Learning Group, Technische Universit\u00e4t Berlin, Berlin, Germany]","institution_ids":["https://openalex.org/I4577782"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5014060431","display_name":"Nico G\u00f6rnitz","orcid":"https://orcid.org/0000-0002-5222-3631"},"institutions":[{"id":"https://openalex.org/I4577782","display_name":"Technische Universit\u00e4t Berlin","ror":"https://ror.org/03v4gjf40","country_code":"DE","type":"education","lineage":["https://openalex.org/I4577782"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Nico Gornitz","raw_affiliation_strings":["Machine Learning Group, Technische Universit\u00e4t Berlin, Berlin, Germany","Machine Learning Group, Technische Universit\u00e4t Berlin Berlin, Germany"],"raw_orcid":"https://orcid.org/0000-0002-5222-3631","affiliations":[{"raw_affiliation_string":"Machine Learning Group, Technische Universit\u00e4t Berlin, Berlin, Germany","institution_ids":["https://openalex.org/I4577782"]},{"raw_affiliation_string":"Machine Learning Group, Technische Universit\u00e4t Berlin Berlin, Germany","institution_ids":["https://openalex.org/I4577782"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5107838719","display_name":"Klaus\u2010Robert M\u00fcller","orcid":null},"institutions":[{"id":"https://openalex.org/I197347611","display_name":"Korea University","ror":"https://ror.org/047dqcg40","country_code":"KR","type":"education","lineage":["https://openalex.org/I197347611"]},{"id":"https://openalex.org/I4210109712","display_name":"Max Planck Institute for Informatics","ror":"https://ror.org/01w19ak89","country_code":"DE","type":"facility","lineage":["https://openalex.org/I149899117","https://openalex.org/I4210109712"]},{"id":"https://openalex.org/I4577782","display_name":"Technische Universit\u00e4t Berlin","ror":"https://ror.org/03v4gjf40","country_code":"DE","type":"education","lineage":["https://openalex.org/I4577782"]}],"countries":["DE","KR"],"is_corresponding":false,"raw_author_name":"Klaus-Robert Muller","raw_affiliation_strings":["Berlin Big Data Center, Machine Learning Group, Technische Universit\u00e4t Berlin, Berlin, Germany","Department of Brain and Cognitive Engineering, Korea University, Seoul, South Korea","Max Planck Institute for Informatics, Saarbr\u00fccken, Germany","[Berlin Big Data Center, Machine Learning Group, Technische Universit\u00e4t Berlin, Berlin, Germany]"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Berlin Big Data Center, Machine Learning Group, Technische Universit\u00e4t Berlin, Berlin, Germany","institution_ids":["https://openalex.org/I4577782"]},{"raw_affiliation_string":"Department of Brain and Cognitive Engineering, Korea University, Seoul, South Korea","institution_ids":["https://openalex.org/I197347611"]},{"raw_affiliation_string":"Max Planck Institute for Informatics, Saarbr\u00fccken, Germany","institution_ids":["https://openalex.org/I4210109712"]},{"raw_affiliation_string":"[Berlin Big Data Center, Machine Learning Group, Technische Universit\u00e4t Berlin, Berlin, Germany]","institution_ids":["https://openalex.org/I4577782"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.0038985,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"31","issue":"7","first_page":"1","last_page":"5"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10181","display_name":"Natural Language Processing Techniques","score":0.9980999827384949,"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/T10181","display_name":"Natural Language Processing Techniques","score":0.9980999827384949,"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/T10028","display_name":"Topic Modeling","score":0.996999979019165,"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/T11269","display_name":"Algorithms and Data Compression","score":0.994700014591217,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/parsing","display_name":"Parsing","score":0.8444122076034546},{"id":"https://openalex.org/keywords/margin","display_name":"Margin (machine learning)","score":0.8373437523841858},{"id":"https://openalex.org/keywords/discriminative-model","display_name":"Discriminative model","score":0.8071095943450928},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7599081993103027},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6920321583747864},{"id":"https://openalex.org/keywords/measure","display_name":"Measure (data warehouse)","score":0.546187162399292},{"id":"https://openalex.org/keywords/sequence","display_name":"Sequence (biology)","score":0.5190854072570801},{"id":"https://openalex.org/keywords/structured-prediction","display_name":"Structured prediction","score":0.5177637338638306},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.5045379400253296},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.49932098388671875},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4877358376979828},{"id":"https://openalex.org/keywords/function","display_name":"Function (biology)","score":0.4814264476299286},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.4664095640182495},{"id":"https://openalex.org/keywords/property","display_name":"Property (philosophy)","score":0.45746877789497375},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.441354364156723},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.39439865946769714},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.2012469470500946}],"concepts":[{"id":"https://openalex.org/C186644900","wikidata":"https://www.wikidata.org/wiki/Q194152","display_name":"Parsing","level":2,"score":0.8444122076034546},{"id":"https://openalex.org/C774472","wikidata":"https://www.wikidata.org/wiki/Q6760393","display_name":"Margin (machine learning)","level":2,"score":0.8373437523841858},{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.8071095943450928},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7599081993103027},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6920321583747864},{"id":"https://openalex.org/C2780009758","wikidata":"https://www.wikidata.org/wiki/Q6804172","display_name":"Measure (data warehouse)","level":2,"score":0.546187162399292},{"id":"https://openalex.org/C2778112365","wikidata":"https://www.wikidata.org/wiki/Q3511065","display_name":"Sequence (biology)","level":2,"score":0.5190854072570801},{"id":"https://openalex.org/C22367795","wikidata":"https://www.wikidata.org/wiki/Q7625208","display_name":"Structured prediction","level":2,"score":0.5177637338638306},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.5045379400253296},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.49932098388671875},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4877358376979828},{"id":"https://openalex.org/C14036430","wikidata":"https://www.wikidata.org/wiki/Q3736076","display_name":"Function (biology)","level":2,"score":0.4814264476299286},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.4664095640182495},{"id":"https://openalex.org/C189950617","wikidata":"https://www.wikidata.org/wiki/Q937228","display_name":"Property (philosophy)","level":2,"score":0.45746877789497375},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.441354364156723},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.39439865946769714},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.2012469470500946},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C78458016","wikidata":"https://www.wikidata.org/wiki/Q840400","display_name":"Evolutionary biology","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C54355233","wikidata":"https://www.wikidata.org/wiki/Q7162","display_name":"Genetics","level":1,"score":0.0}],"mesh":[],"locations_count":5,"locations":[{"id":"doi:10.1109/tnnls.2019.2934225","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tnnls.2019.2934225","pdf_url":null,"source":{"id":"https://openalex.org/S4210175523","display_name":"IEEE Transactions on Neural Networks and Learning Systems","issn_l":"2162-237X","issn":["2162-237X","2162-2388"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Neural Networks and Learning Systems","raw_type":"journal-article"},{"id":"pmid:31494564","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/31494564","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE transactions on neural networks and learning systems","raw_type":null},{"id":"pmh:oai:arXiv.org:1709.01562","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1709.01562","pdf_url":"https://arxiv.org/pdf/1709.01562","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":null},{"id":"mag:2752432813","is_oa":true,"landing_page_url":"https://arxiv.org/pdf/1709.01562.pdf","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"arXiv (Cornell University)","raw_type":null},{"id":"doi:10.48550/arxiv.1709.01562","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.1709.01562","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:1709.01562","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1709.01562","pdf_url":"https://arxiv.org/pdf/1709.01562","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":null},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/10","score":0.7599999904632568,"display_name":"Reduced inequalities"}],"awards":[{"id":"https://openalex.org/G1553489635","display_name":null,"funder_award_id":"01IS14013A.","funder_id":"https://openalex.org/F4320321114","funder_display_name":"Bundesministerium f\u00fcr Bildung und Forschung"},{"id":"https://openalex.org/G2156757918","display_name":null,"funder_award_id":"2017-0-00451","funder_id":"https://openalex.org/F4320335489","funder_display_name":"Institute for Information and Communications Technology Promotion"},{"id":"https://openalex.org/G5655345859","display_name":null,"funder_award_id":"10032745","funder_id":"https://openalex.org/F4320324094","funder_display_name":"Technische Universit\u00e4t Berlin"}],"funders":[{"id":"https://openalex.org/F4320321114","display_name":"Bundesministerium f\u00fcr Bildung und Forschung","ror":"https://ror.org/04pz7b180"},{"id":"https://openalex.org/F4320324094","display_name":"Technische Universit\u00e4t Berlin","ror":"https://ror.org/03v4gjf40"},{"id":"https://openalex.org/F4320335489","display_name":"Institute for Information and Communications Technology Promotion","ror":"https://ror.org/01g0hqq23"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2752432813.pdf","grobid_xml":"https://content.openalex.org/works/W2752432813.grobid-xml"},"referenced_works_count":42,"referenced_works":["https://openalex.org/W147273232","https://openalex.org/W220623884","https://openalex.org/W1506806321","https://openalex.org/W1518470882","https://openalex.org/W1551104980","https://openalex.org/W1632114991","https://openalex.org/W1877183374","https://openalex.org/W1970961429","https://openalex.org/W1989926363","https://openalex.org/W2008652694","https://openalex.org/W2031248101","https://openalex.org/W2069808690","https://openalex.org/W2070771761","https://openalex.org/W2092423930","https://openalex.org/W2097606805","https://openalex.org/W2097826433","https://openalex.org/W2105636360","https://openalex.org/W2105644991","https://openalex.org/W2105842272","https://openalex.org/W2111753845","https://openalex.org/W2116410915","https://openalex.org/W2131962941","https://openalex.org/W2142384583","https://openalex.org/W2250993494","https://openalex.org/W2343505200","https://openalex.org/W2512425033","https://openalex.org/W2564486991","https://openalex.org/W2963084773","https://openalex.org/W2963462075","https://openalex.org/W2964262905","https://openalex.org/W4301229630","https://openalex.org/W6605963652","https://openalex.org/W6632973184","https://openalex.org/W6635452821","https://openalex.org/W6639316738","https://openalex.org/W6675760969","https://openalex.org/W6675783020","https://openalex.org/W6677054210","https://openalex.org/W6681199723","https://openalex.org/W6686210315","https://openalex.org/W6691599203","https://openalex.org/W6980340173"],"related_works":["https://openalex.org/W2126903356","https://openalex.org/W2571687794","https://openalex.org/W2605078375","https://openalex.org/W2964176578","https://openalex.org/W1985839258","https://openalex.org/W2477720715","https://openalex.org/W2096748209","https://openalex.org/W2606657333","https://openalex.org/W2566283430","https://openalex.org/W2029441559","https://openalex.org/W3020539438","https://openalex.org/W2013966960","https://openalex.org/W2762970261","https://openalex.org/W2016352809","https://openalex.org/W2367638993","https://openalex.org/W2739634393","https://openalex.org/W2839756932","https://openalex.org/W2152993039","https://openalex.org/W1738364571","https://openalex.org/W2048701710"],"abstract_inverted_index":{"Many":[0],"learning":[1],"tasks":[2],"in":[3,80,180],"the":[4,32,41,47,51,56,65,75,78,81,103,114,118,125,129,135,146,163,166,174,188],"field":[5],"of":[6,24,31,44,59,67,84,93,177],"natural":[7],"language":[8],"processing":[9],"including":[10],"sequence":[11,13],"tagging,":[12],"segmentation,":[14],"and":[15,70,184],"syntactic":[16],"parsing":[17,69],"have":[18],"been":[19],"successfully":[20],"approached":[21],"by":[22,144,150],"means":[23],"structured":[25,204],"prediction":[26,182],"methods.":[27],"An":[28],"appealing":[29],"property":[30],"corresponding":[33,104,119],"training":[34,115],"algorithms":[35],"is":[36,97,122,132],"their":[37],"ability":[38],"to":[39,55,73,101,192,202],"integrate":[40],"loss":[42,120,164,175,205],"function":[43,121,176],"interest":[45,178],"into":[46],"optimization":[48],"process":[49],"improving":[50],"final":[52],"results":[53],"according":[54],"chosen":[57],"measure":[58],"performance.":[60],"Here,":[61,139],"we":[62,140,155],"focus":[63],"on":[64,124,134,165],"task":[66],"constituency":[68],"show":[71],"how":[72],"optimize":[74],"model":[76],"for":[77],"F1-score":[79],"max-margin":[82],"framework":[83],"a":[85,98,111],"structural":[86],"support":[87],"vector":[88],"machine":[89],"(SVM).":[90],"For":[91],"reasons":[92],"computational":[94,189],"efficiency,":[95],"it":[96],"common":[99],"approach":[100,171],"binarize":[102],"grammar":[105],"before":[106],"training.":[107],"Unfortunately,":[108],"this":[109,142],"introduces":[110],"bias":[112],"during":[113],"procedure":[116,148],"as":[117],"evaluated":[123],"binary":[126],"representation,":[127],"while":[128],"resulting":[130,179],"performance":[131],"measured":[133],"original":[136],"unbinarized":[137,167],"trees.":[138,168],"address":[141],"problem":[143],"extending":[145],"inference":[147],"presented":[149,196],"Bauer":[151],"et":[152],"al.":[153],"Specifically,":[154],"propose":[156],"an":[157],"algorithmic":[158],"modification":[159],"that":[160],"allows":[161],"evaluating":[162],"The":[169,195],"new":[170],"properly":[172],"models":[173],"better":[181],"accuracy":[183],"still":[185],"benefits":[186],"from":[187],"efficiency":[190],"due":[191],"binarized":[193],"representation.":[194],"idea":[197],"can":[198],"be":[199],"easily":[200],"transferred":[201],"other":[203],"functions.":[206]},"counts_by_year":[],"updated_date":"2026-08-01T09:00:35.917206","created_date":"2025-10-10T00:00:00"}
