Bohan Wang
Bohan Wang
Joint Ph.D. Student, University of Science and Technology of China and Microsoft Research Aisa
Vahvistettu sähköpostiosoite verkkotunnuksessa - Kotisivu
The implicit bias for adaptive optimization algorithms on homogeneous neural networks
B Wang, Q Meng, W Chen, TY Liu
International Conference on Machine Learning, 10849-10858, 2021
Piecewise linear activations substantially shape the loss surfaces of neural networks
F He*, B Wang*, D Tao
International Conference on Learning Representations (ICLR) 2020, 2020
Machine-learning nonconservative dynamics for new-physics detection
Z Liu, B Wang, Q Meng, W Chen, M Tegmark, TY Liu
Physical Review E 104 (5), 055302, 2021
Provable adaptivity in adam
B Wang, Y Zhang, H Zhang, Q Meng, ZM Ma, TY Liu, W Chen
arXiv preprint arXiv:2208.09900, 2022
Convergence of adagrad for non-convex objectives: Simple proofs and relaxed assumptions
B Wang, H Zhang, Z Ma, W Chen
The Thirty Sixth Annual Conference on Learning Theory, 161-190, 2023
Creating training sets via weak indirect supervision
J Zhang, B Wang, X Song, Y Wang, Y Yang, J Bai, A Ratner
ICLR 2022, 0
Tighter generalization bounds for iterative differentially private learning algorithms
F He*, B Wang*, D Tao
Uncertainty in Artificial Intelligence (UAI) 2021, 2021
Does Momentum Change the Implicit Regularization on Separable Data?
B Wang, Q Meng, H Zhang, R Sun, W Chen, ZM Ma
Neurips 2022, 0
Closing the gap between the upper bound and lower bound of Adam's iteration complexity
B Wang, J Fu, H Zhang, N Zheng, W Chen
Advances in Neural Information Processing Systems 36, 2024
Robustness, privacy, and generalization of adversarial training
F He, S Fu, B Wang, D Tao
arXiv preprint arXiv:2012.13573, 2020
On the trade-off of intra-/inter-class diversity for supervised pre-training
J Zhang, B Wang, Z Hu, PWW Koh, AJ Ratner
Advances in Neural Information Processing Systems 36, 2024
-GNN: incorporating ring priors into molecular modeling
J Zhu, K Wu, B Wang, Y Xia, S Xie, Q Meng, L Wu, T Qin, W Zhou, H Li, ...
The Eleventh International Conference on Learning Representations, 2023
Optimizing Information-theoretical Generalization Bounds via Anisotropic Noise in SGLD
B Wang, H Zhang, J Zhang, Q Meng, W Chen, TY Liu
35th Conference on Neural Information Processing Systems (Neurips 2021), 2021
When and why momentum accelerates sgd: An empirical study
J Fu, B Wang, H Zhang, Z Zhang, W Chen, N Zheng
arXiv preprint arXiv:2306.09000, 2023
Fast conditional mixing of mcmc algorithms for non-log-concave distributions
X Cheng, B Wang, J Zhang, Y Zhu
Advances in Neural Information Processing Systems 36, 2024
Large Catapults in Momentum Gradient Descent with Warmup: An Empirical Study
P Phunyaphibarn, J Lee, B Wang, H Zhang, C Yun
arXiv preprint arXiv:2311.15051, 2023
Towards Understanding the Riemannian SGD and SVRG Flows on Wasserstein Probabilistic Space
M Yi, B Wang
arXiv preprint arXiv:2401.13530, 2024
Fast conditional mixing of MCMC algorithms for non-log-concave distributions
B Wang, X Cheng, J Zhang, Y Zhu
Proceedings of the 37th International Conference on Neural Information …, 2023
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