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Holden Lee
Holden Lee
Assistant Professor of Applied Mathematics and Statistics, Johns Hopkins University
Verified email at jhu.edu - Homepage
Title
Cited by
Cited by
Year
Spectral filtering for general linear dynamical systems
E Hazan, H Lee, K Singh, C Zhang, Y Zhang
Advances in Neural Information Processing Systems 31, 2018
772018
On the ability of neural nets to express distributions
H Lee, R Ge, T Ma, A Risteski, S Arora
Conference on Learning Theory 2017., 2017
772017
Explaining landscape connectivity of low-cost solutions for multilayer nets
R Kuditipudi, X Wang, H Lee, Y Zhang, Z Li, W Hu, R Ge, S Arora
Advances in neural information processing systems 32, 2019
582019
Beyond log-concavity: Provable guarantees for sampling multi-modal distributions using simulated tempering langevin monte carlo
H Lee, A Risteski, R Ge
Advances in neural information processing systems 31, 2018
37*2018
Towards provable control for unknown linear dynamical systems
S Arora, E Hazan, H Lee, K Singh, C Zhang, Y Zhang
232018
No-regret prediction in marginally stable systems
U Ghai, H Lee, K Singh, C Zhang, Y Zhang
COLT 2020 - The 33rd Annual Conference on Learning Theory, July 9-12, 2020., 2020
172020
Simulated tempering langevin monte carlo ii: An improved proof using soft markov chain decomposition
R Ge, H Lee, A Risteski
arXiv preprint arXiv:1812.00793, 2018
142018
Pixie: a social chatbot
O Adewale, A Beatson, D Buniatyan, J Ge, M Khodak, H Lee, N Prasad, ...
Alexa prize proceedings, 2017
132017
Estimating normalizing constants for log-concave distributions: Algorithms and lower bounds
R Ge, H Lee, J Lu
Proceedings of the 52nd Annual ACM SIGACT Symposium on Theory of Computing …, 2020
112020
Convergence for score-based generative modeling with polynomial complexity
H Lee, J Lu, Y Tan
arXiv preprint arXiv:2206.06227, 2022
92022
Robust guarantees for learning an autoregressive filter
H Lee, C Zhang
Algorithmic Learning Theory, 490-517, 2020
92020
Improved rates for identification of partially observed linear dynamical systems
H Lee
arXiv preprint arXiv:2011.10006, 2020
92020
-Adic properties of partition functions
E Belmont, H Lee, A Musat, S Trebat-Leder
Monatshefte für Mathematik 173 (1), 1-34, 2014
82014
Universal Approximation for Log-concave Distributions using Well-conditioned Normalizing Flows
H Lee, C Pabbaraju, A Sevekari, A Risteski
arXiv preprint arXiv:2107.02951, 2021
6*2021
Online sampling from log-concave distributions
H Lee, O Mangoubi, N Vishnoi
Advances in Neural Information Processing Systems 32, 2019
62019
Convergence of score-based generative modeling for general data distributions
H Lee, J Lu, Y Tan
arXiv preprint arXiv:2209.12381, 2022
42022
Sampling Approximately Low-Rank Ising Models: MCMC meets Variational Methods
F Koehler, H Lee, A Risteski
Conference on Learning Theory, 4945-4988, 2022
32022
Improved rates for prediction and identification of partially observed linear dynamical systems
H Lee
International Conference on Algorithmic Learning Theory, 668-698, 2022
32022
Extracting latent state representations with linear dynamics from rich observations
A Frandsen, R Ge, H Lee
International Conference on Machine Learning, 6705-6725, 2022
12022
Efficient sampling from the Bingham distribution
R Ge, H Lee, J Lu, A Risteski
Algorithmic Learning Theory, 673-685, 2021
12021
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Articles 1–20