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Jun-Kun Wang
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Year
On frank-wolfe and equilibrium computation
JD Abernethy, JK Wang
Advances in Neural Information Processing Systems 30, 2017
412017
Faster rates for convex-concave games
J Abernethy, K Lai, K Levy, JK Wang
Conference on Learning Theory, 2018
392018
Acceleration through optimistic no-regret dynamics
JK Wang, JD Abernethy
Advances in Neural Information Processing Systems 31, 2018
362018
Escaping saddle points faster with stochastic momentum
JK Wang, CH Lin, J Abernethy
arXiv preprint arXiv:2106.02985, 2021
122021
A Modular Analysis of Provable Acceleration via Polyak's Momentum: Training a Wide ReLU Network and a Deep Linear Network
JK Wang, CH Lin, J Abernethy
Proceedings of the 38th International Conference on Machine Learning, 2021
102021
Revisiting projection-free optimization for strongly convex constraint sets
J Rector-Brooks, JK Wang, B Mozafari
Proceedings of the AAAI Conference on Artificial Intelligence 33 (01), 1576-1583, 2019
72019
Robust inverse covariance estimation under noisy measurements
JK Wang
International Conference on Machine Learning, 928-936, 2014
72014
An optimistic acceleration of amsgrad for nonconvex optimization
JK Wang, X Li, B Karimi, P Li
Asian Conference on Machine Learning, 422-437, 2021
32021
No-Regret Dynamics in the Fenchel Game: A Unified Framework for Algorithmic Convex Optimization
JK Wang, J Abernethy, KY Levy
arXiv preprint arXiv:2111.11309, 2021
32021
Quickly finding a benign region via heavy ball momentum in non-convex optimization
JK Wang, J Abernethy
arXiv preprint arXiv:2010.01449, 2020
22020
Parallel Least-Squares Policy Iteration
JK Wang, SD Lin
2016 IEEE International Conference on Data Science and Advanced Analytics …, 2016
22016
Accelerating Hamiltonian Monte Carlo via Chebyshev Integration Time
JK Wang, A Wibisono
arXiv preprint arXiv:2207.02189, 2022
12022
Online Linear Optimization with Sparsity Constraints
JK Wang, CJ Lu, SD Lin
Algorithmic Learning Theory, 883-897, 2019
12019
Provable Acceleration of Heavy Ball beyond Quadratics for a Class of Polyak-Lojasiewicz Functions when the Non-Convexity is Averaged-Out
JK Wang, CH Lin, A Wibisono, B Hu
International Conference on Machine Learning, 2022
2022
Understanding How Over-Parametrization Leads to Acceleration: A case of learning a single teacher neuron
JK Wang, J Abernethy
Asian Conference on Machine Learning, 17-32, 2021
2021
Efficient Sampling-based ADMM for Distributed Data
JK Wang, SD Lin
2016 IEEE International Conference on Data Science and Advanced Analytics …, 2016
2016
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