Xavier Amatriain

11568 Abonné

I build awesome teams to tackle complex problems with a big business impact. Currently starting a startup in the Healthcare/AI space. I enjoy working on the cross-roads of data mining, machine learning, software engineering, innovation, and agile methods. I have 10+ years of experience in research, research management & software engineering. I have authored more than 50 papers in books, journals and international conferences. I have managed different kinds of research teams and projects: from the CLAM Open Source Framework, to the Allosphere project at UCSB. I enjoy seeing and discussing the big picture and the business impact as much as diving into all sorts of technical details. I am...

machine learning recommender systems netflix quora big data healthcare research systems recommender ai data mining recsys search clam telefonica covid-19 healthtech personalization music web audio filtering collaborative data science www2016 nlp distributed systems user modeling social networks context recsys09 software social noise prize product management coronavirus covid telemedicine deep learning startups leadership management technology medicine user experience #machinelearning algorithms devops recsys2014 #kdd2014 rec architecture recsys2012 ratings recommendation systems mobile sigir2010 segementation recommendation time implicit feedback recommmender systems natural noise information ismir c frameworks mir retrieval free ucdarnet source award multimedia open framework acm networks internet agile scrum programming extreme allosphere 3d vr immersion future semantic descriptors youtube lod mining data magic barrier natural experts sigir09

Tout plus

Présentations
Documents
Infographies

Plus récents Les plus populaires

Xavier Amatriain

10 more lessons learned from building Machine Learning systems

Recommender Systems (Machine Learning Summer School 2014 @ CMU)

10 more lessons learned from building Machine Learning systems - MLConf

10 Lessons Learned from Building Machine Learning Systems

Kdd 2014 Tutorial - the recommender problem revisited

Machine Learning to Grow the World's Knowledge

Recsys 2014 Tutorial - The Recommender Problem Revisited

Netflix Recommendations - Beyond the 5 Stars

Building Large-scale Real-world Recommender Systems - Recsys2012 tutorial

The Science and the Magic of User Feedback for Recommender Systems

Lessons learned from building practical deep learning systems

Lean DevOps - Lessons Learned from Innovation-driven Companies

Recsys 2016 tutorial: Lessons learned from building real-life recommender systems

Qcon SF 2013 - Machine Learning & Recommender Systems @ Netflix Scale

Past, present, and future of Recommender Systems: an industry perspective

Media, data, context... and the Holy Grail of User Taste Prediction

Staying Shallow & Lean in a Deep Learning World

Past present and future of Recommender Systems: an Industry Perspective

Medical advice as a Recommender System

Machine Learning for Q&A Sites: The Quora Example