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X-WR-CALNAME;VALUE=TEXT:Eventi DIAG
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TZID:Europe/Paris
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DTSTART:20251026T030000
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UID:calendar.29376.field_data.0@www.open.diag.uniroma1.it
DTSTAMP:20260404T211230Z
CREATED:20250618T155326Z
DESCRIPTION:AbstractSchool choice mechanisms determine how students are ass
 igned to public schools\, striving to balance individual preferences\, sch
 ool priorities\, and broader goals of fairness. While simple\, well-studie
 d algorithms have strong theoretical guarantees\, real-world applications 
 face practical constraints and policy goals that complicate implementation
 . We focus on three challenges in modern school choice systems: determinin
 g the optimal length of student preference lists\, designing the allocatio
 n of reserved seats\, and targeting scholarship allocations to support dis
 advantaged students. For these problems\, we explore how data can be used 
 to come up with relevant models\, and how solutions to the latter lead to 
 policy recommendations. Based on works with Swati Gupta (MIT)\, Aapeli Vuo
 rinen (Columbia) and Xuan Zhang (Meta).
DTSTART;TZID=Europe/Paris:20250627T120000
DTEND;TZID=Europe/Paris:20250627T120000
LAST-MODIFIED:20250618T172832Z
LOCATION:DIAG - Sapienza\, Aula B203
SUMMARY:Data-driven Decision-making in School Matching - Priof. Yuri Faenza
  (Columbia University)
URL;TYPE=URI:http://www.open.diag.uniroma1.it/node/29376
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