Material Detail

Large Scale Recommender System for The One Class Problem

Large Scale Recommender System for The One Class Problem

This video was recorded at Large-scale Online Learning and Decision Making (LSOLDM) Workshop, Cumberland Lodge 2012. The goal of this workshop is to bring together researchers from both industry and academia to share their experiences of implementing large-scale applications of online learning and online decision-making. A selection of example applications includes banner advertisement selection, news story selection, targeted email, and recommender systems. The workshop will focus on the scalability of current online methods to large-scale implementations that are of practical value to industry. Relevant methods include exploration/exploitation trade-offs (e.g. contextual bandits), large-scale gradient descent, parallelization, collaborative filtering, unsupervised feature learning and dimensionality reduction. For more information visit the Workshop website.

Quality

  • User Rating
  • Comments
  • Learning Exercises
  • Bookmark Collections
  • Course ePortfolios
  • Accessibility Info

More about this material

Comments

Log in to participate in the discussions or sign up if you are not already a MERLOT member.