Daniil Dmitriev @dmitrievdaniil7
PhD student at ETH Zurich working on robustness, privacy and random matrix theory. daniildmitriev.github.io Zurich Joined July 2018-
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Daniil Dmitriev retweeted
Open Postdoctoral position in Privacy (and unlearning) and Robustness in Machine Learning in University of Copenhagen to work with me! If you want to spend a couple of years working on these exciting topics in beautiful Copenhagen, Apply here employment.ku.dk/all-vacancies/…
Open Postdoctoral position in Privacy (and unlearning) and Robustness in Machine Learning in University of Copenhagen to work with me! If you want to spend a couple of years working on these exciting topics in beautiful Copenhagen, Apply here employment.ku.dk/all-vacancies/… https://t.co/tTPlWfN7v5
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Daniil Dmitriev retweeted
Very happy that this paper was accepted to #COLT2024 on the separation between private and non-private online learnability. Joint work with @dmitrievdaniil7 and Kristof Szabo. There are still few open problems that remain to fully settle this question :)
Very happy that this paper was accepted to #COLT2024 on the separation between private and non-private online learnability. Joint work with @dmitrievdaniil7 and Kristof Szabo. There are still few open problems that remain to fully settle this question :)
Daniil Dmitriev retweeted
The call for this position is now public. This will be jointly supervised with Prof. Amir Yehudayoff at @DIKU_Institut , Prof. Varun Kanade @CompSciOxford (including a stay in Oxford for 3-6 months), and myself. candidate.hr-manager.net/ApplicationIni… RTs appreciated
The call for this position is now public. This will be jointly supervised with Prof. Amir Yehudayoff at @DIKU_Institut , Prof. Varun Kanade @CompSciOxford (including a stay in Oxford for 3-6 months), and myself. candidate.hr-manager.net/ApplicationIni… RTs appreciated
Daniil Dmitriev retweeted
2 concurrent papers, one by @inhaleopenair, @minilek, Lyu, Stemmer and Sarlós () & the other by us solve our open problem presented in #COLT2022. (See @GolowichNoah & Livni's upper bound) Interestingly, both have the same hard instance in the lower bound.
2 concurrent papers, one by @inhaleopenair, @minilek, Lyu, Stemmer and Sarlós () & the other by us solve our open problem presented in #COLT2022. (See @GolowichNoah & Livni's upper bound) Interestingly, both have the same hard instance in the lower bound.
Daniil Dmitriev retweeted
Excited about this new preprint with Daniil and @kristo arxiv.org/abs/2402.16778 We show a Ω(log T) lower bound for Differentially Private Online learning, even for finite Littlestone classes. This shows a separation between DP and non-DP online learning in mistake bound model.
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