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Cervezartistas Brew House
Aaron Gutierrez
Georgina Muñoz
Roberto Gutiérrez
Gabriel Alejos
Aldo Cano
Mariana Gutiérrez
Héctor Martinez
DOXA - Amorphica
Aaron Gutierrez
Georgina Muñoz
Roberto Gutiérrez
Gabriel Alejos
Aldo Cano
Mariana Gutiérrez
Héctor Martinez
FinData day
Alistair Croll (Solve For Interesting), Juan Huerta (Goldman Sachs Consumer Lending Group), Robert Passarella (Protege Partners), Giannina Segnini (Journalism School, Columbia University), Mar Cabra (International Consortium of Investigative Journalists), Anand Sanwal (CB Insights), Michael Casey (MIT Media Lab), Diane Chang (Intuit), Jeff McMillan (Morgan Stanley), Tanvi Singh (Credit Suisse), Kelley Yohe (Swift Capital), Michelle Bonat (Data Simply), Susan Woodward (Sand Hill Econometrics), Robert Passarella (Protege Partners)
217 Proyecto Camino Verde
Amorphica //
Comunidades Emergentes
2013-2014
www.facebook.com/EmergentCommunities
Regenerar, unificar y mejorar comunidades estimulando y fomentando el desarrollo inteligente mediante la construcción, planeación, rescate y rehabilitación de espacios públicos dentro de proyectos integrales y sostenibles. Participar activamente en el desarrollo de herramientas para estos fines así como proporcionar capacitación y asesoría profesional a quienes quieran desarrollar e implementar este tipo de proyectos en su propia comunidad.
Lars Peter Hansen, 2013 Nobel laureate, is a world-class researcher in economic dynamics, econometrics and uncertainty. In this talk, taking place at the Chicago Booth Hong Kong Center, he discussed the impact of uncertainty on markets and the economy.
263 Biennale di Venezia
253 Escalinatas Calle Segunda - Tijuana, Centro
Amorphica Design Research Office
Aaron Gutiérrez
Georgina Muñoz
Roberto Gutiérrez
Gabriel Alejos
Aldo Cano
Machine learning techniques are being actively pursued in the private sector and have been widely adopted in fields such as computational biology and computer vision. However, the role of machine learning in economics has so far been limited. This workshop was organized to provide a forum to discuss how ideas and techniques from machine learning could be applied to economic questions. The workshop will bring together researchers from computer science, statistics, econometrics and applied economics to foster interactions and discuss different perspectives on statistical learning and its potential impact on economics.
The workshop began with overview talks on machine learning and statistics by researchers from outside of economics. Three following sessions were organized around the themes of causal inference, prediction, and networks and complex data. Each session included the presentation of papers in economics that make use of machine learning methodology, followed by a discussion by researchers from multiple communities.