{"id":"https://openalex.org/W2171921574","doi":null,"title":"Unsupervised Learning of Sparse and Invariant Features Hierarchies","display_name":"Unsupervised Learning of Sparse and Invariant Features Hierarchies","publication_year":1998,"publication_date":"1998-01-01","ids":{"openalex":"https://openalex.org/W2171921574","mag":"2171921574"},"language":"en","primary_location":{"id":"pmh:oai:CiteSeerX.psu:10.1.1.105.5380","doi":null,"is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.105.5380","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://snowbird.djvuzone.org/abstracts/179.pdf","raw_type":"text"},"volume":null,"type":"conference-abstract","is_traditional":false,"indexed_in":[],"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/A5070477596","display_name":"Y-Lan Boureau","orcid":"https://orcid.org/0009-0008-3990-5778","observed_orcids":["https://orcid.org/0009-0008-3990-5778"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Y-Lan Boureau","raw_affiliation_strings":[],"raw_orcid":"https://orcid.org/0009-0008-3990-5778","affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5113902826","display_name":"Fu Jie Huang","orcid":"https://orcid.org/0000-0002-0985-1042","observed_orcids":["https://orcid.org/0000-0002-0985-1042"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Fu Jie Huang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5001226970","display_name":"Yann LeCun","orcid":"https://orcid.org/0000-0002-1992-2684","observed_orcids":["https://orcid.org/0000-0002-1992-2684"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yann LeCun","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.6000999808311462,"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"}},"topics":[{"id":"https://openalex.org/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.6000999808311462,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.260699987411499,"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/T10824","display_name":"Image Retrieval and Classification Techniques","score":0.033399999141693115,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/unsupervised-representation-learning","display_name":"unsupervised feature learning","score":0.9649999737739563},{"id":"https://openalex.org/keywords/sparse-features","display_name":"sparse features","score":0.5540000200271606},{"id":"https://openalex.org/keywords/translation-invariance","display_name":"translation invariance","score":0.9190000295639038},{"id":"https://openalex.org/keywords/feature-hierarchy","display_name":"feature hierarchy","score":0.777999997138977},{"id":"https://openalex.org/keywords/max-pooling","display_name":"max pooling","score":0.7580000162124634},{"id":"https://openalex.org/keywords/object-recognition","display_name":"object recognition","score":0.5680000185966492},{"id":"https://openalex.org/keywords/high-dimensional-data","display_name":"high-dimensional data","score":0.6650000214576721}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5691327452659607},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.44701117277145386},{"id":"https://openalex.org/C190470478","wikidata":"https://www.wikidata.org/wiki/Q2370229","display_name":"Invariant (physics)","level":2,"score":0.41300126910209656},{"id":"https://openalex.org/C8038995","wikidata":"https://www.wikidata.org/wiki/Q1152135","display_name":"Unsupervised learning","level":2,"score":0.4126039147377014},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.39866432547569275},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.37771371006965637},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3506571650505066},{"id":"https://openalex.org/C37914503","wikidata":"https://www.wikidata.org/wiki/Q156495","display_name":"Mathematical physics","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:oai:CiteSeerX.psu:10.1.1.105.5380","doi":null,"is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.105.5380","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://snowbird.djvuzone.org/abstracts/179.pdf","raw_type":"text"},{"id":"mag:2171921574","doi":null,"is_oa":false,"landing_page_url":"http://snowbird.djvuzone.org/2007/abstracts/179.pdf","pdf_url":null,"source":null,"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":2,"referenced_works":["https://openalex.org/W407547601","https://openalex.org/W2112796928"],"related_works":["https://openalex.org/W2139427956","https://openalex.org/W44791420","https://openalex.org/W2301105015","https://openalex.org/W1650052828","https://openalex.org/W7095131037","https://openalex.org/W7097814207","https://openalex.org/W104211377","https://openalex.org/W7097717706","https://openalex.org/W7096776147","https://openalex.org/W2333904056"],"abstract_inverted_index":{"Unsupervised":[0],"learning":[1,160,182],"methods":[2,20],"are":[3,194],"commonly":[4],"used":[5],"to":[6,98,132],"produce":[7],"feature":[8,75,81],"extractors":[9],"in":[10,53,58,109,113,137],"image":[11],"analysis":[12],"systems.":[13],"A":[14],"challenging":[15],"question":[16],"is":[17,49,154,213],"whether":[18],"these":[19,151],"can":[21],"learn":[22],"invariant":[23],"hierarchies":[24,183],"of":[25,34,72,80,87,184],"features.":[26,189],"This":[27],"would":[28],"make":[29],"much":[30],"easier":[31],"the":[32,51,115,120,127,139,161,171],"problem":[33],"extracting":[35],"useful":[36],"information":[37],"from":[38,126],"very":[39],"high":[40],"dimensional":[41],"datasets":[42],"with":[43],"few":[44],"labeled":[45],"samples,":[46],"as":[47],"it":[48],"often":[50],"case":[52],"many":[54],"object":[55,104],"recognition":[56,100,105],"tasks":[57],"computer":[59],"vision.":[60],"The":[61],"feed-forward,":[62],"multi-stage":[63],"Hubel":[64],"and":[65,77,102,118,186,208],"Wiesel":[66],"architecture":[67,141],"[1,2,3,4,5]":[68],"stacks":[69],"multiple":[70,195],"levels":[71],"alternating":[73],"convolutional":[74],"detectors,":[76],"local":[78,206],"pooling":[79,172],"maps":[82],"using":[83,170],"some":[84],"weighted":[85],"average":[86],"units":[88],"within":[89,203],"a":[90,177,200,204,209],"neighborhood.":[91],"These":[92],"models":[93,111],"have":[94],"been":[95],"successfully":[96],"applied":[97],"handwriting":[99],"[1,2],":[101],"generic":[103],"[4,5].":[106],"Learning":[107],"features":[108],"existing":[110],"consists":[112],"handcrafting":[114],"first":[116],"layers":[117,122,173],"training":[119,128,138,146,168],"upper":[121],"by":[123,169,199,216],"recording":[124],"templates":[125],"set,":[129],"which":[130,143],"leads":[131],"inefficient":[133],"representations":[134],"[4,5],":[135],"or":[136],"entire":[140],"supervised,":[142],"requires":[144],"large":[145],"sets":[147],"[2,3].":[148],"In":[149],"all":[150],"models,":[152],"invariance":[153],"never":[155],"taken":[156],"into":[157],"account":[158],"while":[159],"features,":[162],"but":[163],"might":[164],"be":[165],"achieved":[166],"after":[167],"[6].":[174],"We":[175],"propose":[176],"fully":[178],"unsupervised":[179],"algorithm":[180],"for":[181],"sparse":[185],"locally":[187],"shift-invariant":[188],"At":[190],"each":[191],"level,":[192,217],"there":[193],"convolution":[196],"filters":[197],"followed":[198],"max-pooling":[201],"layer":[202],"spatially":[205],"neighborhood,":[207],"sigmoid":[210],"non-linearity.":[211],"Training":[212],"performed":[214],"level":[215],"separately.":[218]},"counts_by_year":[],"updated_date":"2026-11-06T12:05:46.655746","created_date":"2016-06-24T00:00:00"}