October 20th, 2019 - October 20th, 2020
The program will bring together researchers from both academia and industry to study mathematical, statistical and computational aspects of data science and learning, with emphasis on the emerging science of deep learning. The scope of the program will include the following subjects, as well as others:
- Dimensionality reduction and its role in learning
- Information theory and its interplay with computation and learning
- Probability in high dimensions
- Theory of deep learning
The organizers will provide some funding for guests. Typical visits will be one week long, but we also offer more extended visits for excellent Ph.D students and postdocs. For more information, please email the program organizers.
Confirmed visitors: Konstantin Makarychev, Thatchaphol Saranurak, Virginia Vassilevska Williams, Pawel Gawrychowski, Omri Weinstein, David Woodruff, Jelani Nelson, Michael Mahoney, Stephan Horst Sommer, Edo Liberty, Tatiana A. Starikovskaya, Przemek Uznanski,
We look forward to seeing you in our program!
Some of the talks offered by the visitors will be offered in the Technion CS DS/DL Theory Seminar (usually Mondays at 12:30 with refreshments at 12:00), while some will be offered at Bar-Ilan University (date and time – TBD).
We are looking for postdocs!
As part of this program, we are searching for several brilliant postdocs. Candidates are required to have a strong background in theory or in Deep Learning.
The postdoctoral researchers will work both with the research group at the Technion and Bar-Ilan University.
The duration of the fellowship can be anywhere between 1-3 years.
The positions are open until filled, but for full consideration candidates should apply before Mar 1st, 2020 at email@example.com by sending a cv and 2 recommendation letters.
This project has received funding from the European UnionРІР‚в„ўs Horizon 2020 research and innovation program under grant agreement No 682203 -ERC-[ Inf-Speed-Tradeoff ] and under grant agreement No 683064 -ERC- [ Modern Pattern Matching (MPM) ].