{"id":"https://openalex.org/W3199041052","doi":"https://doi.org/10.1109/ijcnn52387.2021.9533863","title":"Towards Unbiased Random Features with Lower Variance For Stationary Indefinite Kernels","display_name":"Towards Unbiased Random Features with Lower Variance For Stationary Indefinite Kernels","publication_year":2021,"publication_date":"2021-07-18","ids":{"openalex":"https://openalex.org/W3199041052","doi":"https://doi.org/10.1109/ijcnn52387.2021.9533863","mag":"3199041052"},"language":"en","primary_location":{"id":"doi:10.1109/ijcnn52387.2021.9533863","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn52387.2021.9533863","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 International Joint Conference on Neural Networks (IJCNN)","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/A5101545534","display_name":"Qin Luo","orcid":"https://orcid.org/0009-0002-2740-813X"},"institutions":[{"id":"https://openalex.org/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Qin Luo","raw_affiliation_strings":["Shanghai Jiao Tong University,Institute of Image Processing and Pattern Recognition,Shanghai,China","Institute of Image Processing and Pattern Recognition, Shanghai Jiao Tong University, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"Shanghai Jiao Tong University,Institute of Image Processing and Pattern Recognition,Shanghai,China","institution_ids":["https://openalex.org/I183067930"]},{"raw_affiliation_string":"Institute of Image Processing and Pattern Recognition, Shanghai Jiao Tong University, Shanghai, China","institution_ids":["https://openalex.org/I183067930"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101435392","display_name":"Kun Fang","orcid":"https://orcid.org/0000-0001-6351-201X"},"institutions":[{"id":"https://openalex.org/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Kun Fang","raw_affiliation_strings":["Shanghai Jiao Tong University,Institute of Image Processing and Pattern Recognition,Shanghai,China","Institute of Image Processing and Pattern Recognition, Shanghai Jiao Tong University, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"Shanghai Jiao Tong University,Institute of Image Processing and Pattern Recognition,Shanghai,China","institution_ids":["https://openalex.org/I183067930"]},{"raw_affiliation_string":"Institute of Image Processing and Pattern Recognition, Shanghai Jiao Tong University, Shanghai, China","institution_ids":["https://openalex.org/I183067930"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100404947","display_name":"Jie Yang","orcid":"https://orcid.org/0000-0003-4801-7162"},"institutions":[{"id":"https://openalex.org/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jie Yang","raw_affiliation_strings":["Shanghai Jiao Tong University,Institute of Image Processing and Pattern Recognition,Shanghai,China","Institute of Image Processing and Pattern Recognition, Shanghai Jiao Tong University, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"Shanghai Jiao Tong University,Institute of Image Processing and Pattern Recognition,Shanghai,China","institution_ids":["https://openalex.org/I183067930"]},{"raw_affiliation_string":"Institute of Image Processing and Pattern Recognition, Shanghai Jiao Tong University, Shanghai, China","institution_ids":["https://openalex.org/I183067930"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5026169938","display_name":"Xiaolin Huang","orcid":"https://orcid.org/0000-0003-4285-6520"},"institutions":[{"id":"https://openalex.org/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaolin Huang","raw_affiliation_strings":["Shanghai Jiao Tong University,Institute of Image Processing and Pattern Recognition,Shanghai,China","Institute of Image Processing and Pattern Recognition, Shanghai Jiao Tong University, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"Shanghai Jiao Tong University,Institute of Image Processing and Pattern Recognition,Shanghai,China","institution_ids":["https://openalex.org/I183067930"]},{"raw_affiliation_string":"Institute of Image Processing and Pattern Recognition, Shanghai Jiao Tong University, Shanghai, China","institution_ids":["https://openalex.org/I183067930"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5101545534"],"corresponding_institution_ids":["https://openalex.org/I183067930"],"apc_list":null,"apc_paid":null,"fwci":0.136,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.54968144,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"8"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12814","display_name":"Gaussian Processes and Bayesian Inference","score":0.9987999796867371,"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/T12814","display_name":"Gaussian Processes and Bayesian Inference","score":0.9987999796867371,"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/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.9930999875068665,"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/T10320","display_name":"Neural Networks and Applications","score":0.991599977016449,"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/kernel","display_name":"Kernel (algebra)","score":0.7716196775436401},{"id":"https://openalex.org/keywords/variance","display_name":"Variance (accounting)","score":0.6516181230545044},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.6058124899864197},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.4543137550354004},{"id":"https://openalex.org/keywords/kernel-method","display_name":"Kernel method","score":0.43863773345947266},{"id":"https://openalex.org/keywords/stationary-process","display_name":"Stationary process","score":0.433319091796875},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.4330856204032898},{"id":"https://openalex.org/keywords/scale","display_name":"Scale (ratio)","score":0.4262408912181854},{"id":"https://openalex.org/keywords/applied-mathematics","display_name":"Applied mathematics","score":0.3967289924621582},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.37627995014190674},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.279056191444397},{"id":"https://openalex.org/keywords/combinatorics","display_name":"Combinatorics","score":0.07840383052825928}],"concepts":[{"id":"https://openalex.org/C74193536","wikidata":"https://www.wikidata.org/wiki/Q574844","display_name":"Kernel (algebra)","level":2,"score":0.7716196775436401},{"id":"https://openalex.org/C196083921","wikidata":"https://www.wikidata.org/wiki/Q7915758","display_name":"Variance (accounting)","level":2,"score":0.6516181230545044},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.6058124899864197},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.4543137550354004},{"id":"https://openalex.org/C122280245","wikidata":"https://www.wikidata.org/wiki/Q620622","display_name":"Kernel method","level":3,"score":0.43863773345947266},{"id":"https://openalex.org/C110405555","wikidata":"https://www.wikidata.org/wiki/Q1192209","display_name":"Stationary process","level":2,"score":0.433319091796875},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4330856204032898},{"id":"https://openalex.org/C2778755073","wikidata":"https://www.wikidata.org/wiki/Q10858537","display_name":"Scale (ratio)","level":2,"score":0.4262408912181854},{"id":"https://openalex.org/C28826006","wikidata":"https://www.wikidata.org/wiki/Q33521","display_name":"Applied mathematics","level":1,"score":0.3967289924621582},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.37627995014190674},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.279056191444397},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.07840383052825928},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C144133560","wikidata":"https://www.wikidata.org/wiki/Q4830453","display_name":"Business","level":0,"score":0.0},{"id":"https://openalex.org/C121955636","wikidata":"https://www.wikidata.org/wiki/Q4116214","display_name":"Accounting","level":1,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ijcnn52387.2021.9533863","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn52387.2021.9533863","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 International Joint Conference on Neural Networks (IJCNN)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G2997539743","display_name":null,"funder_award_id":"61977046,61876107,U1803261","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":54,"referenced_works":["https://openalex.org/W175700287","https://openalex.org/W227597898","https://openalex.org/W1560724230","https://openalex.org/W1587559447","https://openalex.org/W2027995896","https://openalex.org/W2041263603","https://openalex.org/W2105527258","https://openalex.org/W2109235804","https://openalex.org/W2118585731","https://openalex.org/W2119821739","https://openalex.org/W2123818990","https://openalex.org/W2125849100","https://openalex.org/W2137226992","https://openalex.org/W2139999468","https://openalex.org/W2144902422","https://openalex.org/W2146897752","https://openalex.org/W2147118250","https://openalex.org/W2170912685","https://openalex.org/W2182347905","https://openalex.org/W2267483825","https://openalex.org/W2271586515","https://openalex.org/W2534193021","https://openalex.org/W2543033259","https://openalex.org/W2544176167","https://openalex.org/W2777010360","https://openalex.org/W2783173735","https://openalex.org/W2786571656","https://openalex.org/W2804074107","https://openalex.org/W2809090039","https://openalex.org/W2891531300","https://openalex.org/W2945461886","https://openalex.org/W2949384808","https://openalex.org/W2962910688","https://openalex.org/W2972538304","https://openalex.org/W3127836906","https://openalex.org/W3158244344","https://openalex.org/W4239510810","https://openalex.org/W6607141589","https://openalex.org/W6675784843","https://openalex.org/W6677656871","https://openalex.org/W6679072756","https://openalex.org/W6680532697","https://openalex.org/W6680783158","https://openalex.org/W6681302627","https://openalex.org/W6686103840","https://openalex.org/W6693905314","https://openalex.org/W6728794588","https://openalex.org/W6728809436","https://openalex.org/W6747382581","https://openalex.org/W6748261976","https://openalex.org/W6752495264","https://openalex.org/W6762772730","https://openalex.org/W6765649955","https://openalex.org/W6790123125"],"related_works":["https://openalex.org/W2089892314","https://openalex.org/W1603091392","https://openalex.org/W4386075310","https://openalex.org/W2095626363","https://openalex.org/W2169565408","https://openalex.org/W2127229869","https://openalex.org/W3123056048","https://openalex.org/W2129978300","https://openalex.org/W2150638158","https://openalex.org/W2121506664"],"abstract_inverted_index":{"Random":[0],"Fourier":[1],"Features":[2],"(RFF)":[3],"demonstrate":[4],"well-appreciated":[5],"performance":[6],"in":[7,127],"kernel":[8,104],"approximation":[9,98,105,109,125],"for":[10,23,34],"large-scale":[11],"situations":[12],"but":[13,55],"restrict":[14],"kernels":[15,37,89],"to":[16,32,43,52,110],"be":[17,30],"stationary":[18,35,54],"and":[19,88,97,118,134],"positive":[20],"definite.":[21],"And":[22],"non-stationary":[24],"kernels,":[25,114],"the":[26,39,44,72,102,111,128],"corresponding":[27],"RFF":[28],"could":[29],"converted":[31],"that":[33,91],"indefinite":[36,56],"when":[38],"inputs":[40],"are":[41,60],"restricted":[42],"unit":[45],"sphere.":[46],"Numerous":[47],"methods":[48],"provide":[49],"accessible":[50],"ways":[51],"approximate":[53],"kernels.":[57],"However,":[58],"they":[59],"either":[61],"biased":[62],"or":[63],"possess":[64],"large":[65],"variance.":[66,82],"In":[67],"this":[68],"article,":[69],"we":[70],"propose":[71],"generalized":[73],"orthogonal":[74],"random":[75],"features,":[76],"an":[77],"unbiased":[78],"estimation":[79],"with":[80,101,123],"lower":[81,95],"Experimental":[83],"results":[84],"on":[85],"various":[86],"datasets":[87],"verify":[90],"our":[92,124],"algorithm":[93,126],"achieves":[94],"variance":[96],"error":[99],"compared":[100],"existing":[103],"methods.":[106],"With":[107],"better":[108],"originally":[112],"selected":[113],"improved":[115],"classification":[116],"accuracy":[117],"regression":[119],"ability":[120],"is":[121],"obtained":[122],"framework":[129],"of":[130],"support":[131],"vector":[132],"machine":[133],"regression.":[135]},"counts_by_year":[{"year":2022,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}