Academic staff
Researcher interests: Probabilistic Graphical Models. Fundamental representations and methods for inference and learning in large scale domains, with an emphasis on high-level elements such as structure learning, the discovery of hidden variables and classes, transfer of knowledge between related classes/tasks. I have recently taken a particular interest to nonlinear high-dimensional representation of continuous or hybrid distributions. Real-life Applications. Applying fundamental techniques to challenging domains such as computational biology and machine vision. Recently, my I have started focusing on the development of principled techniques based on probabilistic knowledge for diagnosis in the field of medical informatics.
FACULTY / SCHOOL: Faculty of Social Sciences
DEPARTMENT: Statistics
Contact Business Development: Tamir Huberman

Selected Publications

Amir Globerson, amit daniely, deborah cohen, Gal Elidan
learning with rules (2018)| arXiv preprint arXiv:1803.03155| Read more
ajai tirumali, Avinatan Hassidim, Gal Elidan, guy shalev, mor schlesinger, oleg zlydenko, pete giencke, ran elyaniv, sella nevo, vova anisimov, Ami Wiesel, yossi matias, yotam gigi, zach moshe
ml for flood forecasting at scale (2018)| arXiv: Learning| Read more
Avinatan Hassidim, Gal Elidan, guy shalev, sella nevo, Ami Wiesel, yossi matias, yotam gigi, zach moshe
towards global remote discharge estimation using the few to estimate the many (2018)| arXiv preprint arXiv:1901.00786| Read more
craig boutilier, dale schuurmans, Gal Elidan, martin mladenov, Ofer Meshi, tyler
logistic markov decision processes (2017)| Twenty-Sixth International Joint Conference on Artificial Intelligence| Read more
Gal Elidan, Ami Wiesel, Yonatan Woodbridge
signal detection in complex structured para normal noise (2017)| IEEE Transactions on Signal Processing| Read more
craig boutilier, dale schuurmans, Gal Elidan, martin mladenov, Ofer Meshi, tyler
approximate linear programming for logistic markov decision processes (2017)| | Read more
Gal Elidan, Ami Wiesel, Yonatan Woodbridge
quaternion structured paranormal distributions (2016)| 2016 50th Asilomar Conference on Signals, Systems and Computers| Read more
Gal Elidan, Ami Wiesel, Yonatan Woodbridge
signal detection in para complex normal noise (2016)| 2016 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)| Read more
scalable learning of non decomposable objectives ()| international conference on artificial intelligence and statistics| Read more
large scale learning with global non decomposable objectives ()| arXiv: Machine Learning| Read more

Contact for more information:

Tamir Huberman
CIO
+972-2-6586678
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