Alexander Gray

Alexander Gray
CTO, Skytree, Inc.

Website | @skytreeHQ

Dr. Gray obtained degrees in Applied Mathematics and Computer Science from Berkeley and a PhD in Computer Science from Carnegie Mellon, and is an Associate Professor at Georgia Tech. His lab works to scale up all of the major practical methods of machine learning (ML) to massive datasets. He began working on this problem at NASA in 1993 (long before the current fashionable talk of “big data”). His large-scale algorithms helped enable the Top Scientific Breakthrough of 2003, and have won a number of research awards. He is a member of the National Academy of Sciences Committee on the Analysis of Massive Data and frequently gives invited tutorial lectures on massive-scale ML at top research conferences and agencies.

Sessions

Sponsored Session, Ballroom G
Alexander Gray (Skytree, Inc.)
Average rating: ***..
(3.50, 2 ratings)
Machine learning (ML) holds the key to the most advanced uses of big data. But is ML really possible on big data with state-of-the-art methods, or just simple ones? Can ML really be done in real time today? Is MapReduce the right answer? The cloud? I will review the current state of ML technology both at the research level and the industry-readiness level, and current best solution options. Read more.

Sponsors

  • EMC
  • Microsoft
  • HPCC Systems™ from LexisNexis® Risk Solutions
  • MarkLogic
  • Shared Learning Collaborative
  • Cloudera
  • Digital Reasoning Systems
  • Pentaho
  • Rackspace Hosting
  • Teradata Aster
  • VMware
  • IBM
  • NetApp
  • Oracle
  • 1010data
  • 10gen
  • Acxiom
  • Amazon Web Services
  • Calpont
  • Cisco
  • Couchbase
  • Cray
  • Datameer
  • DataSift
  • DataStax
  • Esri
  • Facebook
  • Feedzai
  • Hadapt
  • Hortonworks
  • Impetus
  • Jaspersoft
  • Karmasphere
  • Lucid Imagination
  • MapR Technologies
  • Pervasive
  • Platform Computing
  • Revolution Analytics
  • Scaleout Software
  • Skytree, Inc.
  • Splunk
  • Tableau Software
  • Talend

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