{"id":"https://openalex.org/W6903497486","doi":"https://doi.org/10.13016/twct-cnxl","title":"FOUNDATIONS OF TRUSTWORTHY DEEP LEARNING: FAIRNESS, ROBUSTNESS, AND EXPLAINABILITY","display_name":"FOUNDATIONS OF TRUSTWORTHY DEEP LEARNING: FAIRNESS, ROBUSTNESS, AND EXPLAINABILITY","publication_year":2024,"publication_date":"2024-01-01","ids":{"openalex":"https://openalex.org/W6903497486","doi":"https://doi.org/10.13016/twct-cnxl"},"language":"en","primary_location":{"id":"pmh:oai:drum.lib.umd.edu:1903/32859","is_oa":true,"landing_page_url":"http://hdl.handle.net/1903/32859","pdf_url":"https://drum.lib.umd.edu/bitstreams/6fcce3c6-d977-4dd6-9bf2-ba914648e5ca/download","source":{"id":"https://openalex.org/S4306401518","display_name":"University Libraries (University of Maryland)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I66946132","host_organization_name":"University of Maryland, College Park","host_organization_lineage":["https://openalex.org/I66946132"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Dissertation"},"type":"dissertation","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://drum.lib.umd.edu/bitstreams/6fcce3c6-d977-4dd6-9bf2-ba914648e5ca/download","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Nanda, Vedant","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Nanda, Vedant","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":true,"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":true,"primary_topic":{"id":"https://openalex.org/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.8485000133514404,"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/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.8485000133514404,"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/T10883","display_name":"Ethics and Social Impacts of AI","score":0.11289999634027481,"subfield":{"id":"https://openalex.org/subfields/3311","display_name":"Safety Research"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T12026","display_name":"Explainable Artificial Intelligence (XAI)","score":0.014499999582767487,"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/adversarial-system","display_name":"Adversarial system","score":0.7615000009536743},{"id":"https://openalex.org/keywords/trustworthiness","display_name":"Trustworthiness","score":0.6344000101089478},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.5645999908447266},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.4481000006198883},{"id":"https://openalex.org/keywords/scope","display_name":"Scope (computer science)","score":0.44350001215934753},{"id":"https://openalex.org/keywords/foundation","display_name":"Foundation (evidence)","score":0.4092000126838684}],"concepts":[{"id":"https://openalex.org/C37736160","wikidata":"https://www.wikidata.org/wiki/Q1801315","display_name":"Adversarial system","level":2,"score":0.7615000009536743},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6496000289916992},{"id":"https://openalex.org/C153701036","wikidata":"https://www.wikidata.org/wiki/Q659974","display_name":"Trustworthiness","level":2,"score":0.6344000101089478},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.5645999908447266},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4487000107765198},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4481000006198883},{"id":"https://openalex.org/C2778012447","wikidata":"https://www.wikidata.org/wiki/Q1034415","display_name":"Scope (computer science)","level":2,"score":0.44350001215934753},{"id":"https://openalex.org/C2780966255","wikidata":"https://www.wikidata.org/wiki/Q5474306","display_name":"Foundation (evidence)","level":2,"score":0.4092000126838684},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.40459999442100525},{"id":"https://openalex.org/C112930515","wikidata":"https://www.wikidata.org/wiki/Q4389547","display_name":"Risk analysis (engineering)","level":1,"score":0.37139999866485596},{"id":"https://openalex.org/C2780428219","wikidata":"https://www.wikidata.org/wiki/Q16952335","display_name":"Cover (algebra)","level":2,"score":0.3666999936103821},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.3400999903678894},{"id":"https://openalex.org/C2776608160","wikidata":"https://www.wikidata.org/wiki/Q4785462","display_name":"Natural (archaeology)","level":2,"score":0.33799999952316284},{"id":"https://openalex.org/C539667460","wikidata":"https://www.wikidata.org/wiki/Q2414942","display_name":"Management science","level":1,"score":0.2985000014305115},{"id":"https://openalex.org/C78780964","wikidata":"https://www.wikidata.org/wiki/Q7233193","display_name":"Position paper","level":2,"score":0.26910001039505005},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.25}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:oai:drum.lib.umd.edu:1903/32859","is_oa":true,"landing_page_url":"http://hdl.handle.net/1903/32859","pdf_url":"https://drum.lib.umd.edu/bitstreams/6fcce3c6-d977-4dd6-9bf2-ba914648e5ca/download","source":{"id":"https://openalex.org/S4306401518","display_name":"University Libraries (University of Maryland)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I66946132","host_organization_name":"University of Maryland, College Park","host_organization_lineage":["https://openalex.org/I66946132"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Dissertation"},{"id":"doi:10.13016/twct-cnxl","is_oa":true,"landing_page_url":"https://doi.org/10.13016/twct-cnxl","pdf_url":null,"source":{"id":"https://openalex.org/S4306402644","display_name":"Digital Repository at the University of Maryland (University of Maryland College Park)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I66946132","host_organization_name":"University of Maryland, College Park","host_organization_lineage":["https://openalex.org/I66946132"],"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":"Collection"}],"best_oa_location":{"id":"pmh:oai:drum.lib.umd.edu:1903/32859","is_oa":true,"landing_page_url":"http://hdl.handle.net/1903/32859","pdf_url":"https://drum.lib.umd.edu/bitstreams/6fcce3c6-d977-4dd6-9bf2-ba914648e5ca/download","source":{"id":"https://openalex.org/S4306401518","display_name":"University Libraries (University of Maryland)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I66946132","host_organization_name":"University of Maryland, College Park","host_organization_lineage":["https://openalex.org/I66946132"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Dissertation"},"sustainable_development_goals":[{"score":0.7893230319023132,"display_name":"Peace, Justice and strong institutions","id":"https://metadata.un.org/sdg/16"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W6903497486.pdf"},"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Deep":[0],"Learning":[1],"(DL)":[2,199],"models,":[3,12,84,247],"especially":[4,203],"with":[5,266],"the":[6,9,47,55,64,73,80,112,140,182,221,236,259,310,325,372],"rise":[7],"of":[8,49,66,82,98,114,116,137,163,173,223,256,261,263,269,296,301,313,336,363],"so-called":[10],"foundation":[11],"are":[13],"increasingly":[14],"used":[15],"in":[16,44,90,148,170,324,360,371],"real-world":[17,164],"applications":[18,165],"either":[19],"as":[20,25,152,272],"autonomous":[21],"systems":[22],"(\\eg~facial":[23],"recognition),":[24],"decision":[26],"aids":[27],"(\\eg~medical":[28],"imaging,":[29],"writing":[30],"assistants),":[31],"and":[32,102,125,157,209,287,289,316],"even":[33,332],"to":[34,72,78,110,122,205,211,225,243,348],"generate":[35],"novel":[36],"content":[37],"(\\eg~chatbots,":[38],"image":[39],"generators).":[40],"This":[41,75,366],"naturally":[42],"results":[43],"concerns":[45],"about":[46,194],"trustworthiness":[48],"these":[50,67,117,131],"systems,":[51],"for":[52,60,196],"example,":[53],"do":[54],"models":[56,68,124,150,224,265,268,286,315],"systematically":[57],"perform":[58],"worse":[59],"certain":[61],"subgroups?":[62],"Are":[63],"outputs":[65],"reliable":[69],"under":[70],"perturbations":[71],"inputs?":[74],"thesis":[76],"aims":[77],"strengthen":[79],"foundations":[81],"DL":[83,123,179,264,285,292,314],"so":[85],"they":[86],"can":[87,307,344],"be":[88],"trusted":[89],"deployment.":[91],"I":[92,104,185,239,274,328],"will":[93,105,186,240,275,329],"cover":[94],"three":[95],"important":[96],"aspects":[97,118],"trust:":[99],"fairness,":[100],"robustness,":[101],"explainability.":[103],"argue":[106,241],"that":[107,190,242,279,375],"we":[108,248,306,358],"need":[109],"expand":[111],"scope":[113],"each":[115],"when":[119],"applying":[120],"them":[121],"carefully":[126,226],"consider":[127],"possible":[128],"tradeoffs":[129],"between":[130,283,291],"desirable":[132],"but":[133],"sometimes":[134],"conflicting":[135],"notions":[136],"trust.":[138],"Traditionally":[139],"fairness":[141,195],"community":[142],"has":[143,216],"worked":[144],"on":[145,219,251],"mitigating":[146],"biases":[147],"classical":[149],"such":[151,271],"Support":[153],"Vector":[154],"Machines":[155],"(SVMs)":[156],"logistic":[158],"regression.":[159],"However,":[160],"a":[161,171,252,299,333,341,361],"lot":[162],"where":[166],"bias":[167],"shows":[168],"up":[169],"myriad":[172],"ways":[174],"involve":[175],"much":[176],"more":[177,253],"complicated":[178],"models.":[180,293],"In":[181,235],"first":[183],"part,":[184,238,327],"present":[187,276],"two":[188,277],"works":[189,278],"show":[191,330],"how":[192,331],"thinking":[193],"deep":[197],"learning":[198],"introduces":[200],"new":[201],"challenges,":[202],"due":[204],"their":[206],"overparametrized":[207],"nature":[208],"susceptibility":[210],"adversarial":[212],"attacks.":[213],"Robustness":[214],"literature":[215,374],"focused":[217],"largely":[218],"measuring":[220,258],"invariance":[222],"constructed":[227],"(adversarial":[228],"attacks)":[229],"or":[230],"natural":[231],"(distribution":[232],"shifts)":[233],"noise.":[234],"second":[237],"get":[244],"truly":[245,320],"robust":[246,321],"must":[249],"focus":[250],"general":[254],"notion":[255],"robustness:":[257],"alignment":[260],"invariances":[262,282],"other":[267],"perception":[270],"humans.":[273],"measure":[280,300],"shared":[281],"(1)":[284],"humans,":[288],"(2)":[290],"Such":[294],"measurements":[295],"robustness":[297],"provide":[298],"\\textit{relative":[302],"robustness},":[303],"through":[304],"which":[305,357],"better":[308],"understand":[309],"failure":[311],"modes":[312],"work":[317],"towards":[318],"building":[319],"systems.":[322],"Finally,":[323],"third":[326],"small":[334],"subset":[335],"randomly":[337],"chosen":[338],"neurons":[339,378],"from":[340],"pre-trained":[342,364],"representation":[343],"transfer":[345],"very":[346],"well":[347],"downstream":[349],"tasks.":[350],"We":[351],"call":[352],"this":[353],"phenomenon":[354],"\\textit{diffused":[355],"redundancy},":[356],"observe":[359],"variety":[362],"representations.":[365],"finding":[367],"challenges":[368],"existing":[369],"beliefs":[370],"explainability":[373],"claim":[376],"individual":[377],"learn":[379],"disjoint":[380],"semantically":[381],"meaningful":[382],"concepts.":[383]},"counts_by_year":[],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
