Notable Paper Awards

Congratulations to our Notable Papers!  We selected these 7 papers from over 270 submissions based on technical contribution, presentation, and overall significance.  For each Notable Paper, the senior program commitee nominated a discussant; these discussants each wrote a short discussion paper summarizing the Notable Paper's most significant benefits, caveats, and relationships to the broader literature.

We presented awards to the Notable Paper authors at the conference.  Thanks to our sponsors, Google and Microsoft, for funding these awards!

The papers:

• Robert Tillman and Peter Spirtes.  Learning equivalence classes of acyclic models with latent and selection variables from multiple datasets with overlapping variables.  [abs, pdf, discussion]
• Alina Beygelzimer, John Langford, Lihong Li, Lev Reyzin, and Robert Schapire.  Contextual Bandit Algorithms with Supervised Learning Guarantees.  [abs, pdf, discussion]
• Hugo Larochelle and Iain Murray.  The Neural Autoregressive Distribution Estimator.  [abs, pdf, discussion]
• Qiang Liu and Alexander Ihler.  Learning Scale Free Networks by Reweighted L1 regularization.  [abs, pdf, discussion]
• Neil Lawrence.  Spectral Dimensionality Reduction via Maximum Entropy.  [abs, pdf, discussion]
• Frederik Eaton.  A conditional game for comparing approximations.  [abs, pdf, discussion]
• John Paisley, Chong Wang, and David Blei.  The Discrete Infinite Logistic Normal Distribution for Mixed-Membership Modeling.  [abs, pdf, discussion]