{"id":"https://openalex.org/W3202637261","doi":null,"title":"Misclassification-Aware Gaussian Smoothing and Mixed Augmentations improves Robustness against Domain Shifts","display_name":"Misclassification-Aware Gaussian Smoothing and Mixed Augmentations improves Robustness against Domain Shifts","publication_year":2021,"publication_date":"2021-04-02","ids":{"openalex":"https://openalex.org/W3202637261","mag":"3202637261"},"language":"en","primary_location":{"id":"mag:3202637261","doi":null,"is_oa":true,"landing_page_url":"https://arxiv.org/pdf/2104.01231.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,"listed_in":[],"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},"volume":null,"type":"preprint","is_traditional":true,"indexed_in":[],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2104.01231.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5088931370","display_name":"Athanasios Tsiligkaridis","orcid":"https://orcid.org/0000-0002-0048-7803","observed_orcids":["https://orcid.org/0000-0002-0048-7803"]},"institutions":[{"id":"https://openalex.org/I111088046","display_name":"Boston University","ror":"https://ror.org/05qwgg493","country_code":"US","type":"education","lineage":["https://openalex.org/I111088046"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Athanasios Tsiligkaridis","raw_affiliation_strings":["Boston Univ"],"raw_orcid":"https://orcid.org/0000-0002-0048-7803","affiliations":[{"raw_affiliation_string":"Boston Univ","institution_ids":["https://openalex.org/I111088046"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5031789494","display_name":"Theodoros Tsiligkaridis","orcid":"https://orcid.org/0000-0003-0903-2861","observed_orcids":["https://orcid.org/0000-0003-0903-2861"]},"institutions":[{"id":"https://openalex.org/I63966007","display_name":"Massachusetts Institute of Technology","ror":"https://ror.org/042nb2s44","country_code":"US","type":"education","lineage":["https://openalex.org/I63966007"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Theodoros Tsiligkaridis","raw_affiliation_strings":["Massachusetts Institute Of Technology#TAB#"],"raw_orcid":"https://orcid.org/0000-0003-0903-2861","affiliations":[{"raw_affiliation_string":"Massachusetts Institute Of Technology#TAB#","institution_ids":["https://openalex.org/I63966007"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"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/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.8169000148773193,"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":0.8169000148773193,"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.12839999794960022,"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/T12535","display_name":"Machine Learning and Data Classification","score":0.04129999876022339,"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/domain-shift-robustness","display_name":"domain shift robustness","score":0.8450000286102295},{"id":"https://openalex.org/keywords/image-classification","display_name":"image classification","score":0.48899999260902405},{"id":"https://openalex.org/keywords/uncertainty-calibration","display_name":"uncertainty calibration","score":0.7829999923706055},{"id":"https://openalex.org/keywords/corruption","display_name":"corruption","score":0.5860000252723694}],"concepts":[{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.883264422416687},{"id":"https://openalex.org/C3770464","wikidata":"https://www.wikidata.org/wiki/Q775963","display_name":"Smoothing","level":2,"score":0.8763526678085327},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7509448528289795},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.7241401076316833},{"id":"https://openalex.org/C104317376","wikidata":"https://www.wikidata.org/wiki/Q1894545","display_name":"Gaussian blur","level":5,"score":0.6111465096473694},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5925242900848389},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.5244840979576111},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5085726976394653},{"id":"https://openalex.org/C2984842247","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep neural networks","level":3,"score":0.506269097328186},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4997584819793701},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.41140642762184143},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.3889561593532562},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.36733147501945496},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3658672571182251},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3647700548171997},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.24959707260131836},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.15058141946792603},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.14061129093170166},{"id":"https://openalex.org/C106430172","wikidata":"https://www.wikidata.org/wiki/Q6002272","display_name":"Image restoration","level":4,"score":0.10045629739761353},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","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},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"mag:3202637261","doi":null,"is_oa":true,"landing_page_url":"https://arxiv.org/pdf/2104.01231.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,"listed_in":[],"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}],"best_oa_location":{"id":"mag:3202637261","doi":null,"is_oa":true,"landing_page_url":"https://arxiv.org/pdf/2104.01231.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,"listed_in":[],"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},"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":29,"referenced_works":["https://openalex.org/W1677182931","https://openalex.org/W2031342017","https://openalex.org/W2123838014","https://openalex.org/W2163605009","https://openalex.org/W2183341477","https://openalex.org/W2194775991","https://openalex.org/W2560321925","https://openalex.org/W2746314669","https://openalex.org/W2897355816","https://openalex.org/W2901299405","https://openalex.org/W2912237282","https://openalex.org/W2913266441","https://openalex.org/W2937527502","https://openalex.org/W2945033152","https://openalex.org/W2948194985","https://openalex.org/W2949736877","https://openalex.org/W2951940613","https://openalex.org/W2962710014","https://openalex.org/W2963031676","https://openalex.org/W2963060032","https://openalex.org/W2963399829","https://openalex.org/W2963446712","https://openalex.org/W2964253222","https://openalex.org/W2969454448","https://openalex.org/W2970049488","https://openalex.org/W2992308087","https://openalex.org/W2994931756","https://openalex.org/W3009090315","https://openalex.org/W3036438747"],"related_works":["https://openalex.org/W3151999563","https://openalex.org/W4399401461","https://openalex.org/W4385488514","https://openalex.org/W2994088087","https://openalex.org/W4416233645","https://openalex.org/W7133202254","https://openalex.org/W7133193435","https://openalex.org/W4281487767","https://openalex.org/W4415798815","https://openalex.org/W4312313528"],"abstract_inverted_index":{"Deep":[0],"neural":[1],"networks":[2],"achieve":[3],"high":[4,75],"prediction":[5],"accuracy":[6],"when":[7],"the":[8,40,85],"train":[9],"and":[10,26,89,97],"test":[11],"distributions":[12],"coincide.":[13],"In":[14,46],"practice":[15],"though,":[16],"various":[17],"types":[18],"of":[19,42,64,70],"corruptions":[20,71],"can":[21],"deviate":[22],"from":[23],"this":[24,47],"setup":[25],"cause":[27],"severe":[28],"performance":[29],"degradations.":[30],"Few":[31],"methods":[32],"have":[33],"been":[34],"proposed":[35],"to":[36],"address":[37],"generalization":[38],"in":[39,87],"presence":[41],"unforeseen":[43],"domain":[44],"shifts.":[45],"paper,":[48],"we":[49],"propose":[50],"a":[51,68],"misclassification-aware":[52],"Gaussian":[53],"smoothing":[54],"approach,":[55],"coupled":[56],"with":[57],"mixed":[58],"data":[59],"augmentations,":[60],"for":[61],"improving":[62],"robustness":[63,88],"image":[65,94],"classifiers":[66],"against":[67],"variety":[69],"while":[72],"still":[73],"maintaining":[74],"clean":[76],"accuracy.":[77],"We":[78],"show":[79],"that":[80],"our":[81],"method":[82],"improves":[83],"upon":[84],"state-of-the-art":[86],"uncertainty":[90],"calibration":[91],"on":[92],"several":[93],"classification":[95],"benchmarks":[96],"network":[98],"architectures.":[99]},"counts_by_year":[],"updated_date":"2026-11-04T10:54:05.112534","created_date":"2021-10-11T00:00:00"}