Ralf Herbrich
homepage:http://www.herbrich.me/
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Description

Ralf Herbrich is Director of Machine Learning at Amazon. From 2011 to 2012, he worked at Facebook leading the Unified Ranking and Allocation team building large-scale machine learning infrastructure for learning user-action-rate predictors that enabled unified value experiences across Facebook products. From 2009 to 2011, he was Director of Microsoft's Future Social Experiences (FUSE) Lab UK working on the development of computational intelligence technologies on large online data collections. From 2006 to 2010, Ralf was co-leading the Applied Games and Online Services and Advertising group at Microsoft Research Cambridge which engaged in research at the intersection of machine learning and computer games and in the areas of online services, search and online advertising combining insights from machine learning, information retrieval, game theory, artificial intelligence and social network analysis. Ralf joined Microsoft Research in 2000 as a Postdoctoral researcher and Research Fellow of the Darwin College Cambridge. Prior to joining Microsoft, he obtained both a diploma degree in Computer Science in 1997 and a Ph.D. degree in Statistics in 2000 from Technical University of Berlin. Ralf has published over 80 papers and holds over 30 patents. His research interests include Bayesian inference and decision making, kernel methods, statistical learning theory, distributed systems and programming languages. Ralf is one of the inventors of the Drivatars™ system in the Forza Motorsport series as well as the TrueSkill™ ranking and matchmaking system in Xbox 360 Live. He also co-invented the adPredictor click-prediction technology launched in 2009 in Bing's online advertising system.


Lectures:

invited talk
locked flag Learning Sparse Models at Scale
as author at  22nd ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), San Francisco 2016,
1448 views
  invited talk
flag From Theory to Real-World Applications: Technology Transfer in Practice
as author at  The 5th Asian Conference on Machine Learning (ACML), Canberra 2013,
2612 views
tutorial
flag Distributed, Real-Time Bayesian Learning in Online Service
as author at  The 5th Asian Conference on Machine Learning (ACML), Canberra 2013,
3829 views
  lecture
flag Large Scale Online Bayesian Recommendations
as author at  World Wide Web (WWW) Conference, Madrid 2009,
together with: David Stern, Thore Graepel,
7281 views