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.
- David Silver (UCL)
- John Shawe-Taylor (UCL)
- Thore Graepel (Microsoft Research)
- Ralf Herbrich (Facebook)
- John Langford (Microsoft Research, formerly Yahoo! Labs)
- Lihong Li (Microsoft Research, formerly Yahoo! Labs)
- Alina Beygelzimer (IBM Research)