Jingfeng Wu
Orcid: 0009-0009-3414-4487
According to our database1,
Jingfeng Wu
authored at least 40 papers
between 2016 and 2024.
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Bibliography
2024
Nat. Mac. Intell., 2024
CoRR, 2024
Large Stepsize Gradient Descent for Non-Homogeneous Two-Layer Networks: Margin Improvement and Fast Optimization.
CoRR, 2024
In-Context Learning of a Linear Transformer Block: Benefits of the MLP Component and One-Step GD Initialization.
CoRR, 2024
Proceedings of the Service-Oriented Computing - 22nd International Conference, 2024
Proceedings of the Twelfth International Conference on Learning Representations, 2024
Proceedings of the Twelfth International Conference on Learning Representations, 2024
Large Stepsize Gradient Descent for Logistic Loss: Non-Monotonicity of the Loss Improves Optimization Efficiency.
Proceedings of the Thirty Seventh Annual Conference on Learning Theory, June 30, 2024
2023
J. Mach. Learn. Res., 2023
CoRR, 2023
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023
Proceedings of the International Conference on Machine Learning, 2023
Proceedings of the Conference on Lifelong Learning Agents, 2023
2022
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022
The Power and Limitation of Pretraining-Finetuning for Linear Regression under Covariate Shift.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022
Last Iterate Risk Bounds of SGD with Decaying Stepsize for Overparameterized Linear Regression.
Proceedings of the International Conference on Machine Learning, 2022
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022
2021
Proceedings of the ACM SIGCOMM 2021 Conference, Virtual Event, USA, August 23-27, 2021., 2021
Proceedings of the 18th USENIX Symposium on Networked Systems Design and Implementation, 2021
Proceedings of the 18th USENIX Symposium on Networked Systems Design and Implementation, 2021
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021
Accommodating Picky Customers: Regret Bound and Exploration Complexity for Multi-Objective Reinforcement Learning.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021
Direction Matters: On the Implicit Bias of Stochastic Gradient Descent with Moderate Learning Rate.
Proceedings of the 9th International Conference on Learning Representations, 2021
Proceedings of the Asian Conference on Machine Learning, 2021
2020
Direction Matters: On the Implicit Regularization Effect of Stochastic Gradient Descent with Moderate Learning Rate.
CoRR, 2020
Proceedings of the 37th International Conference on Machine Learning, 2020
Proceedings of the 37th International Conference on Machine Learning, 2020
2019
The Multiplicative Noise in Stochastic Gradient Descent: Data-Dependent Regularization, Continuous and Discrete Approximation.
CoRR, 2019
The Anisotropic Noise in Stochastic Gradient Descent: Its Behavior of Escaping from Sharp Minima and Regularization Effects.
Proceedings of the 36th International Conference on Machine Learning, 2019
Proceedings of the Intelligent Computing Theories and Application, 2019
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2019
2018
CoRR, 2018
2017
2016
Research on human body composition prediction model based on Akaike Information Criterion and improved entropy method.
Proceedings of the 9th International Congress on Image and Signal Processing, 2016