Ran El-Yaniv    Ran El-Yaniv


Associate Professor of Computer Science at the Technion.
My research interests include a number of topics in machine learning. I am currently focusing on selective prediction, active learning, financial modeling, and deep (reinforcement) learning.

Research Papers

Current Teaching

Current Graduate Students

Graduated Students


Editorials

I'm an associate editor of the Journal of Artificial Intelligence Research (JAIR), and on the editorial board of the Journal of Machine Learning Research (JMLR).


Conferences

I served as area chair for NIPS 2016, IJCAI 2015, ICML 2013,
and was multiple times on the program committee of various conferences including COLT, ICML, AAAI, ALT and EC.

Book

           Online Computation and Competitive Analysis

Code

  • Deep neural networks with binary weights and activations, as discussed here and here.  Code by Itay Hubara can be found here.
  • STRLET: open source supervised transfer learning toolkit: Java code by Noam Segev can be downloaded here. The toolkit implements various known transfer learning algorithms including our random forest based Structure Transfer and Structure Expansion Reduction algorithms (as discussed here).
  • Sequence prediction using variable order models (as discussed here): Ron Begleiter's Java code can be downloaded here.
  • Some active learning algorithms (as discussed here): Ron Begleiter and Kobi Luz's Java code can be downloaded here.
  • 2D demo of several classification algorithms (including Localized Boosting): Gilad Mishne's Java applet based on Weka can be downloaded here.

Contact

    The best way to reach me is via email: rani at cs dot technion dot ac dot il
    Note that my response time can sometimes be slow. 

    Office: CS Dept. (Taub building), office  526 
    Office phone: (+972)-4-829-3379