R E S E A R C H

Theses

• PhD Thesis: Missing Data Problems in Machine Learning. 2008. [Abstract] [Thesis PDF] [Intro Slides PDF] [Complete Slides PDF]
• Master's Thesis: Collaborative Filtering: A Machine Learning Perspective. 2004. [Abstract] [PDF][PDF Single Space]

Inductive Principles, RBMs and Deep Learning

• Bo Chen, Jo-Anne Ting, Benjamin M. Marlin and Nando de Freitas. Deep Learning of Invariant Spatio-Temporal Features from Video. In Proceedings of the Workshop on Deep Learning and Unsupervised Feature Learning at the 24th Annual Conference on Neural Information Processing Systems, 2010.
• Benjamin M. Marlin, Kevin Swersky, Bo Chen and Nando de Freitas. Inductive Principles for Restricted Boltzmann Machine Learning. Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics. 2010. [Paper PDF] [Poster PDF] [Slides PDF] [Demo] [Data]
• Kevin Swersky, Bo Chen, Benjamin Marlin and Nando de Freitas. A Tutorial on Stochastic Approximation Algorithms for Training Restricted Boltzmann Machines and Deep Belief Nets. Information Theory and Applications Workshop (ITA). 2010. [Paper PDF]
• Bo Chen, Kevin Swersky, Benjamin Marlin and Nando de Freitas. Sparsity Priors and Boosting for Learning Localized Distributed Feature Representations. Technical Report TR-2010-04. University of British Columbia, Department of Computer Science. [Paper PDF]

Structure, Sparsity, and (Latent) Gaussian Graphical Models

• [Oct 17, 2010] Mohammad Emtiyaz Khan, Benjamin M. Marlin, Guillaume Bouchard and Kevin Murphy. Variational Bounds for Mixed-Data Factor Analysis. In Proceedings of the 24th Annual Conference on Neural Information Processing Systems, 2010. [Paper PDF] [Poster PDF] [Code]
• Baback Moghaddam, Benjamin M. Marlin, Emtiyaz Khan, Kevin Murphy. Accelerating Bayesian Structural Inference for Non-Decomposable Gaussian Graphical Models. Proceedings of the Neural Information Processing Systems Conference (NIPS). 2009. [Paper PDF] [Poster PDF]
• Benjamin M. Marlin, Mark Schmidt and Kevin P. Murphy. Group Sparse Priors for Covariance Estimation. Proceedings of the 25th Conference on Uncertainty in Artificial Intelligence. 2009. [Paper PDF] [Poster PDF]
• Benjamin M. Marlin and Kevin P. Murphy. Sparse Gaussian Graphical Models with Unknown Block Structure. Proceedings of the 26th International Conference on Machine Learning. 2009. [Paper PDF] [Slides PDF] [Poster PDF]

Collaborative Filtering with Non-Random Missing Data

• Benjamin M. Marlin and Richard Zemel. Collaborative Prediction and Ranking with Non-Random Missing Data. Proceedings of the 3rd ACM Conference on Recommender Systems. 2009. Winner of best technical paper award. [Paper PDF] [Slides PDF].
• Benjamin M. Marlin, Richard S. Zemel, Sam Roweis, and Malcolm Slaney. Collaborative Filtering and the Missing at Random Assumption. Proceedings of the 23rd Conference on Uncertainty in Artificial Intelligence (UAI2007). [Abstract] [Paper PDF]
• Benjamin Marlin, Richard S. Zemel, and Sam T. Roweis. Unsupervised Learning with Non-ignorable Missing Data. Tenth International Workshop on Artificial Intelligence and Statistics (AISTATS 2005). [Abstract] [Paper PDF]

Collaborative Filtering

• Benjamin Marlin and Richard S. Zemel. The Multiple Multiplicative Factor Model For Collaborative Filtering. In Proc. of the The Twenty-First International Conference on Machine Learning (ICML-2004). pp 576-583. [Abstract] [Paper PDF] [Poster PPT] [Poster PDF]
• Benjamin Marlin. Modeling User Rating Profiles for Collaborative Filtering. In Proc. of the 17th Annual Conference on Neural Information Processing Systems (NIPS-2003). [PDF] [Poster PPT]
• Craig Boutilier, Richard S. Zemel and Benjamin Marlin. Active Collaborative Filtering. In Proc. of the 19th Conference on Uncertainty in Artificial Intelligence (UAI-2003). [PDF]
  
• Active Collaborative Filtering. Demo at Precarn IRIS Conference on Intelligent Systems (IS2003). Halifax, Nova Scotia. June 2003. [Slides PPT]

Computational Geometry

• Benjamin Marlin and Godfried Toussaint. Constructing Convex 3-Polytopes from Two Triangulations of a Polygon. Computational Geometry: Theory and Applications. Volume 28, Issue 1, May 2004, Pages 41-47. [ScienceDirect]
  
• Benjamin Marlin and Godfried Toussaint. Constructing Convex 3-Polytopes from Two Triangulations of a Polygon. Technical Report. School of Computer Science, McGill University, Montreal, Canada, December 2003, SOCS-03.12. [PDF]
  
• Benjamin Marlin and Godfried Toussaint. Constructing Convex 3-Polytopes from Two Triangulations of a Polygon. In Proc. of the 14th annual Canadian Conference on Computational Geometry (CCCG-2002). [Paper PS] [Slides PPT]
  

This site last updated September 12, 2011. © Benjamin M. Marlin