{"id":"https://openalex.org/W2540401547","doi":"https://doi.org/10.1109/globalsip.2013.6736876","title":"ALARM: A logistic auto-regressive model for binary processes on networks","display_name":"ALARM: A logistic auto-regressive model for binary processes on networks","publication_year":2013,"publication_date":"2013-12-01","ids":{"openalex":"https://openalex.org/W2540401547","doi":"https://doi.org/10.1109/globalsip.2013.6736876","mag":"2540401547"},"language":"en","primary_location":{"id":"doi:10.1109/globalsip.2013.6736876","is_oa":false,"landing_page_url":"https://doi.org/10.1109/globalsip.2013.6736876","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2013 IEEE Global Conference on Signal and Information Processing","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/A5064798328","display_name":"Ameya Agaskar","orcid":null},"institutions":[{"id":"https://openalex.org/I2801851002","display_name":"Harvard University Press","ror":"https://ror.org/006v7bf86","country_code":"US","type":"other","lineage":["https://openalex.org/I136199984","https://openalex.org/I2801851002"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Ameya Agaskar","raw_affiliation_strings":["Harvard University, Cambridge, MA, USA"],"affiliations":[{"raw_affiliation_string":"Harvard University, Cambridge, MA, USA","institution_ids":["https://openalex.org/I2801851002"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5038111389","display_name":"Yue M. Lu","orcid":"https://orcid.org/0000-0002-5174-2595"},"institutions":[{"id":"https://openalex.org/I2801851002","display_name":"Harvard University Press","ror":"https://ror.org/006v7bf86","country_code":"US","type":"other","lineage":["https://openalex.org/I136199984","https://openalex.org/I2801851002"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yue M. Lu","raw_affiliation_strings":["Harvard University, Cambridge, MA, USA"],"affiliations":[{"raw_affiliation_string":"Harvard University, Cambridge, MA, USA","institution_ids":["https://openalex.org/I2801851002"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5064798328"],"corresponding_institution_ids":["https://openalex.org/I2801851002"],"apc_list":null,"apc_paid":null,"fwci":0.4989,"has_fulltext":false,"cited_by_count":12,"citation_normalized_percentile":{"value":0.6934974,"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":"305","last_page":"308"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10064","display_name":"Complex Network Analysis Techniques","score":0.9997000098228455,"subfield":{"id":"https://openalex.org/subfields/3109","display_name":"Statistical and Nonlinear Physics"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10064","display_name":"Complex Network Analysis Techniques","score":0.9997000098228455,"subfield":{"id":"https://openalex.org/subfields/3109","display_name":"Statistical and Nonlinear Physics"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T12592","display_name":"Opinion Dynamics and Social Influence","score":0.9987999796867371,"subfield":{"id":"https://openalex.org/subfields/3109","display_name":"Statistical and Nonlinear Physics"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10136","display_name":"Statistical Methods and Inference","score":0.972000002861023,"subfield":{"id":"https://openalex.org/subfields/2613","display_name":"Statistics and Probability"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/autoregressive-model","display_name":"Autoregressive model","score":0.7520878314971924},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6676406860351562},{"id":"https://openalex.org/keywords/alarm","display_name":"ALARM","score":0.5708762407302856},{"id":"https://openalex.org/keywords/binary-number","display_name":"Binary number","score":0.5414095520973206},{"id":"https://openalex.org/keywords/realization","display_name":"Realization (probability)","score":0.5099533796310425},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.5043421983718872},{"id":"https://openalex.org/keywords/node","display_name":"Node (physics)","score":0.46990010142326355},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.36746513843536377},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3422803282737732},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.3338034749031067},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.22603029012680054},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.19077450037002563}],"concepts":[{"id":"https://openalex.org/C159877910","wikidata":"https://www.wikidata.org/wiki/Q2202883","display_name":"Autoregressive model","level":2,"score":0.7520878314971924},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6676406860351562},{"id":"https://openalex.org/C2779119184","wikidata":"https://www.wikidata.org/wiki/Q294350","display_name":"ALARM","level":2,"score":0.5708762407302856},{"id":"https://openalex.org/C48372109","wikidata":"https://www.wikidata.org/wiki/Q3913","display_name":"Binary number","level":2,"score":0.5414095520973206},{"id":"https://openalex.org/C2781089630","wikidata":"https://www.wikidata.org/wiki/Q21856745","display_name":"Realization (probability)","level":2,"score":0.5099533796310425},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.5043421983718872},{"id":"https://openalex.org/C62611344","wikidata":"https://www.wikidata.org/wiki/Q1062658","display_name":"Node (physics)","level":2,"score":0.46990010142326355},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.36746513843536377},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3422803282737732},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.3338034749031067},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.22603029012680054},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.19077450037002563},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.0},{"id":"https://openalex.org/C192562407","wikidata":"https://www.wikidata.org/wiki/Q228736","display_name":"Materials science","level":0,"score":0.0},{"id":"https://openalex.org/C94375191","wikidata":"https://www.wikidata.org/wiki/Q11205","display_name":"Arithmetic","level":1,"score":0.0},{"id":"https://openalex.org/C159985019","wikidata":"https://www.wikidata.org/wiki/Q181790","display_name":"Composite material","level":1,"score":0.0},{"id":"https://openalex.org/C66938386","wikidata":"https://www.wikidata.org/wiki/Q633538","display_name":"Structural engineering","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/globalsip.2013.6736876","is_oa":false,"landing_page_url":"https://doi.org/10.1109/globalsip.2013.6736876","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2013 IEEE Global Conference on Signal and Information Processing","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/3","display_name":"Good health and well-being","score":0.8600000143051147}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":14,"referenced_works":["https://openalex.org/W1544632947","https://openalex.org/W1586505959","https://openalex.org/W1971842701","https://openalex.org/W2012796346","https://openalex.org/W2027197817","https://openalex.org/W2041157860","https://openalex.org/W2068000292","https://openalex.org/W2106398669","https://openalex.org/W2128208871","https://openalex.org/W2138019504","https://openalex.org/W2561238685","https://openalex.org/W3022380717","https://openalex.org/W3098888484","https://openalex.org/W6634951452"],"related_works":["https://openalex.org/W2731305060","https://openalex.org/W2372003537","https://openalex.org/W2022544890","https://openalex.org/W2732807254","https://openalex.org/W2394097730","https://openalex.org/W2587670262","https://openalex.org/W3091941553","https://openalex.org/W3037375888","https://openalex.org/W2366730739","https://openalex.org/W2043523297"],"abstract_inverted_index":{"We":[0,115,140,152],"introduce":[1],"the":[2,21,25,36,51,67,78,85,93,117,134,143,166,169,176,181,185],"ALARM":[3,38,150],"model,":[4],"a":[5,17,31,41,70,98,107,112,130,147,155,172],"logistic":[6,94],"autoregressive":[7],"model":[8,26,121,170],"for":[9,19,122,137],"discrete-time":[10],"binary":[11],"processes":[12],"on":[13,47],"networks,":[14],"and":[15,56,124,128,174],"describe":[16,40],"technique":[18],"learning":[20,146],"graph":[22,148],"structure":[23],"underlying":[24,182],"from":[27,149,171,184],"observations.":[28,151],"Using":[29],"only":[30],"small":[32],"number":[33],"of":[34,44,69,101,119,145,168],"parameters,":[35],"proposed":[37],"can":[39,160],"wide":[42],"range":[43],"dynamic":[45],"behavior":[46,118],"graphs,":[48,127],"such":[49],"as":[50],"contact":[52],"process,":[53,55],"voter":[54],"even":[57],"some":[58],"epidemic":[59],"processes.":[60],"Under":[61],"ALARM,":[62],"at":[63,97],"each":[64],"time":[65,109],"step,":[66],"probability":[68,89],"node":[71],"having":[72],"value":[73],"1":[74],"is":[75,90],"determined":[76],"by":[77,81,92],"values":[79,105],"taken":[80],"its":[82,88,102],"neighbors":[83],"in":[84,133],"past;":[86],"specifically,":[87],"given":[91],"function":[95],"evaluated":[96],"linear":[99],"combination":[100],"neighbors'":[103],"past":[104],"(within":[106],"fixed":[108],"window)":[110],"plus":[111],"bias":[113],"term.":[114],"examine":[116],"this":[120],"1D":[123],"2D":[125,138],"lattice":[126],"observe":[129],"phase":[131],"transition":[132],"steady":[135],"state":[136],"lattices.":[139],"then":[141],"study":[142],"problem":[144],"show":[153],"how":[154],"regularizer":[156],"promoting":[157],"group":[158],"sparsity":[159],"be":[161],"used":[162],"to":[163,179],"efficiently":[164],"learn":[165],"parameters":[167],"realization,":[173],"demonstrate":[175],"resulting":[177],"ability":[178],"reconstruct":[180],"network":[183],"data.":[186]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":2},{"year":2020,"cited_by_count":2},{"year":2019,"cited_by_count":1},{"year":2018,"cited_by_count":1},{"year":2016,"cited_by_count":1},{"year":2015,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
