•   When: Friday, November 09, 2018 from 11:00 AM to 12:00 PM
•   Speakers: Ricardo Baeza-Yates, NTENT & Northeastern University
•   Location: Research Hall 163
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Abstract:
The main problem of deep learning is that most applications of this technique are black boxes and hence is difficult to explain why
a decision was taken. However, in many applications that affect people, the decision must be explained for legal (e.g., GDPR, the
new privacy law of the European Union) and/or ethical reasons (gender or racial bias). We cover the main current techniques to explain machine learning models as well as the challenges involved, ending with best practices and an analysis of the future. 

Bio:
Ricardo Baeza-Yates areas of expertise are web search and data mining, information retrieval, data science and algorithms. Since June 2016, he is CTO of NTENT, a semantic search technology company based in California, USA. He is also the Director of Data Science Programs at Northeastern University, Silicon Valley campus, since August 2017. Before he was VP of Research at Yahoo Labs, based in Barcelona, Spain, and later in Sunnyvale, California, from January 2006 to February 2016. He obtained a Ph.D. in CS from the University of Waterloo, Canada, in 1989. He is co-author of the best-seller Modern Information Retrieval textbook published by Addison-Wesley in 2011 (2nd ed), that won the ASIST 2012 Book of the Year award. From 2002 to 2004 he was elected to the Board of Governors of the IEEE Computer Society and between 2012 and 2016 was elected for the ACM Council. In 2009 he was named ACM Fellow and in 2011 IEEE Fellow, among other awards and distinctions.