{"id":"https://openalex.org/W3110757807","doi":"https://doi.org/10.1145/3400302.3415679","title":"Hessian-driven unequal protection of DNN parameters for robust inference","display_name":"Hessian-driven unequal protection of DNN parameters for robust inference","publication_year":2020,"publication_date":"2020-11-02","ids":{"openalex":"https://openalex.org/W3110757807","doi":"https://doi.org/10.1145/3400302.3415679","mag":"3110757807"},"language":"en","primary_location":{"id":"doi:10.1145/3400302.3415679","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3400302.3415679","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 39th International Conference on Computer-Aided Design","raw_type":"proceedings-article"},"type":"conference-paper","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/A5035180055","display_name":"Saurabh Dash","orcid":"https://orcid.org/0000-0003-2191-8411"},"institutions":[{"id":"https://openalex.org/I130701444","display_name":"Georgia Institute of Technology","ror":"https://ror.org/01zkghx44","country_code":"US","type":"education","lineage":["https://openalex.org/I130701444"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Saurabh Dash","raw_affiliation_strings":["Georgia Institute of Technology"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Georgia Institute of Technology","institution_ids":["https://openalex.org/I130701444"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5009591041","display_name":"Saibal Mukhopadhyay","orcid":"https://orcid.org/0000-0002-8894-3390"},"institutions":[{"id":"https://openalex.org/I130701444","display_name":"Georgia Institute of Technology","ror":"https://ror.org/01zkghx44","country_code":"US","type":"education","lineage":["https://openalex.org/I130701444"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Saibal Mukhopadhyay","raw_affiliation_strings":["Georgia Institute of Technology"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Georgia Institute of Technology","institution_ids":["https://openalex.org/I130701444"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I130701444"],"apc_list":null,"apc_paid":null,"fwci":1.7891,"has_fulltext":false,"cited_by_count":9,"citation_normalized_percentile":{"value":0.85121997,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"9"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10502","display_name":"Advanced Memory and Neural Computing","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10502","display_name":"Advanced Memory and Neural Computing","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T12808","display_name":"Ferroelectric and Negative Capacitance Devices","score":0.9994999766349792,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9987999796867371,"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/hessian-matrix","display_name":"Hessian matrix","score":0.925939679145813},{"id":"https://openalex.org/keywords/metric","display_name":"Metric (unit)","score":0.7348907589912415},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6506890058517456},{"id":"https://openalex.org/keywords/sensitivity","display_name":"Sensitivity (control systems)","score":0.6446046829223633},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.6303660869598389},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5158711671829224},{"id":"https://openalex.org/keywords/fraction","display_name":"Fraction (chemistry)","score":0.507323682308197},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.48740628361701965},{"id":"https://openalex.org/keywords/performance-metric","display_name":"Performance metric","score":0.48167717456817627},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.441707581281662},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.39121219515800476},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.21521365642547607},{"id":"https://openalex.org/keywords/applied-mathematics","display_name":"Applied mathematics","score":0.1717967391014099},{"id":"https://openalex.org/keywords/electronic-engineering","display_name":"Electronic engineering","score":0.13320153951644897},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.11406606435775757}],"concepts":[{"id":"https://openalex.org/C203616005","wikidata":"https://www.wikidata.org/wiki/Q620495","display_name":"Hessian matrix","level":2,"score":0.925939679145813},{"id":"https://openalex.org/C176217482","wikidata":"https://www.wikidata.org/wiki/Q860554","display_name":"Metric (unit)","level":2,"score":0.7348907589912415},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6506890058517456},{"id":"https://openalex.org/C21200559","wikidata":"https://www.wikidata.org/wiki/Q7451068","display_name":"Sensitivity (control systems)","level":2,"score":0.6446046829223633},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.6303660869598389},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5158711671829224},{"id":"https://openalex.org/C149629883","wikidata":"https://www.wikidata.org/wiki/Q660926","display_name":"Fraction (chemistry)","level":2,"score":0.507323682308197},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.48740628361701965},{"id":"https://openalex.org/C2780898871","wikidata":"https://www.wikidata.org/wiki/Q860554","display_name":"Performance metric","level":2,"score":0.48167717456817627},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.441707581281662},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.39121219515800476},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.21521365642547607},{"id":"https://openalex.org/C28826006","wikidata":"https://www.wikidata.org/wiki/Q33521","display_name":"Applied mathematics","level":1,"score":0.1717967391014099},{"id":"https://openalex.org/C24326235","wikidata":"https://www.wikidata.org/wiki/Q126095","display_name":"Electronic engineering","level":1,"score":0.13320153951644897},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.11406606435775757},{"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/C178790620","wikidata":"https://www.wikidata.org/wiki/Q11351","display_name":"Organic chemistry","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/C187736073","wikidata":"https://www.wikidata.org/wiki/Q2920921","display_name":"Management","level":1,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C21547014","wikidata":"https://www.wikidata.org/wiki/Q1423657","display_name":"Operations management","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3400302.3415679","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3400302.3415679","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 39th International Conference on Computer-Aided Design","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":37,"referenced_works":["https://openalex.org/W1972477204","https://openalex.org/W2108598243","https://openalex.org/W2132621842","https://openalex.org/W2141155619","https://openalex.org/W2194775991","https://openalex.org/W2508602506","https://openalex.org/W2518281301","https://openalex.org/W2590016403","https://openalex.org/W2591601611","https://openalex.org/W2613543507","https://openalex.org/W2613989746","https://openalex.org/W2626325961","https://openalex.org/W2735441098","https://openalex.org/W2783000019","https://openalex.org/W2794288888","https://openalex.org/W2801000640","https://openalex.org/W2809624076","https://openalex.org/W2891442728","https://openalex.org/W2899749435","https://openalex.org/W2899771611","https://openalex.org/W2900128795","https://openalex.org/W2920866490","https://openalex.org/W2921329602","https://openalex.org/W2927302606","https://openalex.org/W2946047477","https://openalex.org/W2952429406","https://openalex.org/W2962754331","https://openalex.org/W2963446712","https://openalex.org/W2963452728","https://openalex.org/W2965104923","https://openalex.org/W3016542674","https://openalex.org/W3090986099","https://openalex.org/W4214626551","https://openalex.org/W4236601256","https://openalex.org/W4288626239","https://openalex.org/W4302391768","https://openalex.org/W6759039803"],"related_works":["https://openalex.org/W4361804730","https://openalex.org/W2142113611","https://openalex.org/W2334467465","https://openalex.org/W2018387840","https://openalex.org/W2087870008","https://openalex.org/W2045629210","https://openalex.org/W2162534555","https://openalex.org/W2752178021","https://openalex.org/W2143024819","https://openalex.org/W4247159817"],"abstract_inverted_index":{"This":[0],"paper":[1],"presents":[2],"an":[3],"algorithmic":[4],"approach":[5],"to":[6,55],"design":[7],"reliable":[8],"deep":[9],"neural":[10],"networks":[11],"(DNN)":[12],"in":[13,19,27,30,67,107],"the":[14,20,28,52,59],"presence":[15],"of":[16,91],"stochastic":[17,105],"variations":[18,26,66,106],"network":[21,61],"parameters":[22,62,92],"induced":[23],"by":[24,82],"process":[25],"bit-cells":[29],"a":[31,39,85],"processing-in-memory":[32],"(PIM)":[33],"architecture.":[34],"We":[35],"propose":[36],"and":[37,57],"derive":[38],"Hessian":[40,54],"based":[41],"sensitivity":[42],"metric":[43],"that":[44,81],"can":[45,94],"be":[46],"computed":[47],"without":[48],"computing":[49],"or":[50],"storing":[51],"full":[53],"identify":[56],"protect":[58],"\"important\"":[60],"while":[63],"allowing":[64],"large":[65,103],"unprotected":[68],"parameters.":[69,109],"Experiments":[70],"on":[71,78],"modern":[72],"DNNs":[73],"like":[74],"ResNet,":[75],"MobileNetv2,":[76],"DenseNet":[77],"CIFAR10":[79],"demonstrates":[80],"shielding":[83],"only":[84],"small":[86],"(1%":[87],"--":[88],"5%)":[89],"fraction":[90],"one":[93],"achieve":[95],"less":[96],"than":[97],"1%":[98],"accuracy":[99],"degradation":[100],"even":[101],"under":[102],"(50%)":[104],"other":[108]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":2}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}
