Amir Globerson

Contact

The Rachel and Selim Benin School of Computer Science and Engineering
Ross Building - Room 78A
Givat Ram Campus
The Hebrew University of Jerusalem
email: gamir at cs dot huji dot ac dot il

Tutorial

Slides for the NIPS 2011 tutorial that Tommi Jaakkola and I gave on LP relaxation and graphical models.
Download Part 1
Download Part 2

Code

Download code for our UAI' 08 paper on "Tightening LP Relaxations for MAP using Message Passing"

Publications

Journal papers and Book Chapters

Conference Proceedings

  • Transfer Learning for Constituency-Based Grammars
    Yuan Zhang, Amir Globerson and Regina Barzilay
    Proceedings of the Annual Meeting of the Association for Computational Linguistics (ACL), 2013. To appear.
  • Vanishing Component Analysis
    Roi Livni, David Lehavi, Sagi Schein, Hila Nachlieli, Shai Shalev Shwartz and Amir Globerson
    International Conference on Machine Learning (ICML), 2013. Received the Best Paper Award.
  • An LP view of the M best problem

  • Menachem Fromer and Amir Globerson
    Advances in Neural Information Processing Systems (NIPS) 22, 2009. Received the Outstanding Student Paper Award.
  • Convexifying the Bethe Free Energy

  • Ofer Meshi, Ariel Jaimovich, Amir Globerson and Nir Friedman
    Proceedings of Uncertainty in Artificial Intelligence (UAI). Montreal, Canada. 2009.
  • Convex Learning with Invariances

  • Choon Hui Teo, Amir Globerson , Sam Roweis and Alex Smola
    Advances in Neural Information Processing Systems (NIPS) 20. Vancouver, Canada. 2007.
  • Euclidean Embedding of Co-occurrence data

  • Amir Globerson, Gal Chechik, Fernando Pereira and Naftali Tishby
    Advances in Neural Information Processing Systems (NIPS) 17. Vancouver, Canada. 2004.
    Received the Outstanding Student Paper Award.

PhD Thesis

Technical Reports and Abstracts

  • Information Bounds on Vectors with Applications to Nonstationary and Population Coding

  • Amir Globerson, Eran Stark, Ron Paz, Eilon Vaadia and Naftali Tishby.
    Abstracts of papers presetned at the CSHL 2004 Meeting on Computational and Systems Neuroscience (COSYNE)

Teaching