David Sontag's Home Page

I am a graduate student in Computer Science at MIT. I work with Tommi Jaakkola on approximate inference and learning in probabilistic models. I also work with David Karger on theoretical problems in information retrieval and networking, and with Bonnie Berger in computational biology. I am supported by the Google Fellowship in Machine Learning.

I did my bachelors at UC Berkeley, in Computer Science. While there, I worked with Stuart Russell's First-Order Probabilistic Logic group.

Activities

Publications

Probabilistic inference in graphical models / Combinatorial optimization:

New: Download optimized code implementing our UAI '08 paper.


• D. Sontag, T. Jaakkola. Tree Block Coordinate Descent for MAP in Graphical Models. 12th International Workshop on Artificial Intelligence and Statistics (AI-STATS), April 2009.
• D. Sontag, A. Globerson, T. Jaakkola. Clusters and Coarse Partitions in LP Relaxations. Neural Information Processing Systems (NIPS) 22, Dec. 2008.
• D. Sontag, T. Meltzer, A. Globerson, Y. Weiss, T. Jaakkola. Tightening LP Relaxations for MAP using Message Passing. Uncertainty in Artificial Intelligence (UAI) 24, July 2008. Received best paper award
• D. Sontag, T. Jaakkola. New Outer Bounds on the Marginal Polytope. Neural Information Processing Systems (NIPS) 21, Dec. 2007. Received best student paper award
• D. Sontag. Cutting Plane Algorithms for Variational Inference in Graphical Models. Master's thesis, Massachusetts Institute of Technology, 2007.
  

  Computer networking:

• D. Sontag, Y. Zhang, A. Phanishayee, D. Andersen, D. Karger. Scaling All-Pairs Overlay Routing. To appear in the Fifth ACM International Conference on emerging Networking EXperiments and Technologies (CoNEXT), 2009.
  

  Computational Biology:

• D. Sontag, R. Singh, B. Berger. Probabilistic Modeling of Systematic Errors in Two-Hybrid Experiments. Pacific Symposium on Biocomputing (PSB), 2007. Supplementary information
  

  First-Order Probabilistic Logic:

• B. Milch, B. Marthi, S. Russell, D. Sontag, D. L. Ong, and A. Kolobov. BLOG: Probabilistic Models with Unknown Objects. In Lise Getoor and Ben Taskar, eds. Statistical Relational Learning. Cambridge, MA: MIT Press, 2007.
• B. Milch, B. Marthi, S. Russell, D. Sontag, D. L. Ong, and A. Kolobov. BLOG: Probabilistic Models with Unknown Objects. Proc. 19th International Joint Conference on Artificial Intelligence (IJCAI): 1352-1359, 2005.
• B. Milch, B. Marthi, D. Sontag, S. Russell, D. L. Ong, and A. Kolobov. Approximate Inference for Infinite Contingent Bayesian Networks. 10th International Workshop on Artificial Intelligence and Statistics, 2005.

Past projects:

• Marginalized Kernels for Object Recognition, joint work with Brian Milch for our CS 281B and CS 294 classes (Spring 2004).
• Inference for Relational Web Page Classification, my CS 281A project report (Fall 2003).

Links:

• My father, Eduardo Sontag, and my sister, Laura Sontag.
• Lund University, in Sweden, where I studied abroad in Fall 2004.
• Upsilon Pi Epsilon, the CS honors society at Berkeley, in which I was president in Spring 2005.