IMG-20171004-WA0009

Bio

I am a Computer Science Master’s student at the Technion, Israel, studying under the supervision of Prof. Yuval Filmus. I obtained my Bachelor’s degree in Computer Science from the Technion.

Research interests

I am interested in theoretical computer science, especially in theoretical machine learning and complexity. My recent works are of the topics of information compleity, Huffman codes, multi armed bandits and online algorithms.

Contact information

Email:

yuval.dagan at cs . technion . ac . il

C.V.

Link

Publications

  • Dagan, Y., Filmus, Y., Gabizon, A., & Moran, S. (2017, June). Twenty (simple) questions. In Proceedings of the 49th Annual ACM SIGACT Symposium on Theory of Computing (pp. 9-21). ACM.
    https://arxiv.org/abs/1611.01655
  • Dagan, Y., Filmus, Y., Hatami, H., & Li, Y. (2017, June). Trading information complexity for error. In 32nd Computational Complexity Conference (pp. 16:1-16:59).
    https://arxiv.org/abs/1611.06650
  • Yuval Dagan and Koby Crammer. A Better Resource Allocation Algorithm with Semi-Bandit Feedback. Accepted to the International Conference on Algorithmic Learning Theory (ALT 2018).
    Studies a problem of repeatedly allocating a resource between multiple threads. The allocator has to recognize the better threads and prioritize them accordingly, but the feedback is randomized. We present an algorithm with an asymptotically optimal regret and a matching lower bound. Link

Other research work

  • Yuval Dagan and Saar Zehavi. There is no online sparse regressor with sublinear regret.
    An answer to the main question asked by Dr. Satyen Kale, published in the open problem section of Conference on Learning Theory 2014. We showed that under standard assumptions on hardness of computation, there is no efficient sparse online learning algorithm with sublinear regret. We did not published our result.  Link
  • A problem of repeatedly allocating a resource between multiple threads. The allocator has to recognize the better threads and prioritize them accordingly, but the feedback is randomized. We present an algorithm with an asymptotically optimal regret and a matching lower bound. Link
  • Reuven Cohen, Yuval Dagan and Gabi Nakibly. Procative rerouting in network overlays.
  • A rerouting algorithm for computer networks. Link

Teaching assistance

Role: delivering tutorials, creating and checking homework assignments and exams.

Courses:

  • Introduction to Machine Learning (winter semester 14/15)
  • Automata and Formal Languages (spring semester 14/15, winter semester 15/16)
  • Complexity Theory (spring semester 15/16)
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