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Nataly Brukhim
Nataly Brukhim
Verified email at princeton.edu - Homepage
Title
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Cited by
Year
Following high-level navigation instructions on a simulated quadcopter with imitation learning
V Blukis, N Brukhim, A Bennett, RA Knepper, Y Artzi
arXiv preprint arXiv:1806.00047, 2018
622018
A characterization of multiclass learnability
N Brukhim, D Carmon, I Dinur, S Moran, A Yehudayoff
2022 IEEE 63rd Annual Symposium on Foundations of Computer Science (FOCS …, 2022
34*2022
Boosting for control of dynamical systems
N Agarwal, N Brukhim, E Hazan, Z Lu
International Conference on Machine Learning, 96-103, 2020
19*2020
Projection-free adaptive regret with membership oracles
Z Lu, N Brukhim, P Gradu, E Hazan
International Conference on Algorithmic Learning Theory, 1055-1073, 2023
102023
Online boosting with bandit feedback
N Brukhim, E Hazan
Algorithmic Learning Theory, 397-420, 2021
102021
Predict and constrain: Modeling cardinality in deep structured prediction
N Brukhim, A Globerson
International Conference on Machine Learning, 659-667, 2018
102018
Online agnostic boosting via regret minimization
N Brukhim, X Chen, E Hazan, S Moran
Advances in Neural Information Processing Systems 33, 644-654, 2020
92020
A boosting approach to reinforcement learning
N Brukhim, E Hazan, K Singh
Advances in Neural Information Processing Systems 35, 33806-33817, 2022
62022
Multiclass boosting and the cost of weak learning
N Brukhim, E Hazan, S Moran, I Mukherjee, RE Schapire
Advances in Neural Information Processing Systems 34, 3057-3067, 2021
62021
Improper Multiclass Boosting
N Brukhim, S Hanneke, S Moran
The Thirty Sixth Annual Conference on Learning Theory, 5433-5452, 2023
22023
Multiclass Boosting: Simple and Intuitive Weak Learning Criteria
N Brukhim, A Daniely, Y Mansour, S Moran
Advances in Neural Information Processing Systems 36, 2024
2024
A Unified Model and Dimension for Interactive Estimation
N Brukhim, M Dudik, A Pacchiano, RE Schapire
Advances in Neural Information Processing Systems 36, 2024
2024
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Articles 1–12