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X-WR-CALNAME;VALUE=TEXT:Eventi DIAG
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TZID:Europe/Paris
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DTSTART:20181028T030000
TZOFFSETFROM:+0200
TZOFFSETTO:+0100
RDATE:20191027T030000
TZNAME:CET
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DTSTART:20190331T020000
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UID:calendar.20232.field_data.0@www.glad.uniroma1.it
DTSTAMP:20260411T214110Z
CREATED:20200528T092218Z
DESCRIPTION:AbstractDespite the improvement of AI in the last decades\, the
 re are still tasks very hard for machines\, but easy for humans. Crowdsour
 cing is a computational paradigm that is successfully used to address prob
 lems that require the solution of these types of tasks\, by involving huma
 n workers in the key steps of the computation. An important characteristic
  of human workers is their uniqueness: different workers have different pr
 ofiles and different abilities in solving tasks. During the talk\, there w
 ill be presented new algorithmic solutions\, in the field of Crowdsourcing
 \, that exploit the different levels of expertise of workers\, together wi
 th new results for reducing the recommendation bias\, generated implicitly
  by users\, in the online markets. BiosketchAdriano Fazzone is a postdocto
 ral researcher at DIAG-Sapienza-University-of-Rome\, where he got also a P
 h.D. in 'Engineering in Computer Science'. Adriano's research interests ha
 ve been focused on the design of algorithms for Data-Crowdsourcing problem
 s\, the optimal management of human workers in the online labor market and
 \, recently\, on ensuring algorithmic fairness in recommender systems. 
DTSTART;TZID=Europe/Paris:20190520T140000
DTEND;TZID=Europe/Paris:20190520T140000
LAST-MODIFIED:20210222T211449Z
LOCATION:DIAG - Via Ariosto 25\, Room B203
SUMMARY:Algorithms for Organizing Workers in the Online Labor Market and fo
 r Reducing Recommendation-Bias in Online Markets - Adriano Fazzone\n\n\n  
 \n  \n\n    \n\n\nAdriano\n\n\nFazzone  \n\n  \n\n    \n\n\n\n\n\nesterno
 \n\nstanza: \n\nB219\n\ntelefono: \n\n+39 0677274036  \n\n  \n\n    \n\nIn
 teressi di ricerca: \n\n\n\nData Mining\, Crowdsourcing\n\n\nqualifica_rr:
  \n\nAssistant professors (ricercatori)
URL;TYPE=URI:http://www.glad.uniroma1.it/node/20232
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