Difan Zou
According to our database1,
Difan Zou
authored at least 53 papers
between 2014 and 2024.
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Bibliography
2024
CoRR, 2024
Improving Implicit Regularization of SGD with Preconditioning for Least Square Problems.
CoRR, 2024
An Improved Analysis of Langevin Algorithms with Prior Diffusion for Non-Log-Concave Sampling.
CoRR, 2024
2023
CoRR, 2023
CoRR, 2023
Less is More: On the Feature Redundancy of Pretrained Models When Transferring to Few-shot Tasks.
CoRR, 2023
CoRR, 2023
CoRR, 2023
CoRR, 2023
Proceedings of the International Conference on Machine Learning, 2023
Proceedings of the International Conference on Machine Learning, 2023
Proceedings of the International Conference on Machine Learning, 2023
Understanding the Generalization of Adam in Learning Neural Networks with Proper Regularization.
Proceedings of the Eleventh International Conference on Learning Representations, 2023
The Implicit Bias of Batch Normalization in Linear Models and Two-layer Linear Convolutional Neural Networks.
Proceedings of the Thirty Sixth Annual Conference on Learning Theory, 2023
2022
Understanding the Role of Optimization Algorithms in Learning Over-parameterized Models
PhD thesis, 2022
Two-Dimensional Intensity Distribution and Adaptive Power Allocation for Ultraviolet Ad-Hoc Network.
IEEE Trans. Green Commun. Netw., 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
SIAM J. Sci. Comput., 2021
Faster Convergence of Stochastic Gradient Langevin Dynamics for Non-Log-Concave Sampling.
Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, 2021
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021
Proceedings of the 38th International Conference on Machine Learning, 2021
Proceedings of the 38th International Conference on Machine Learning, 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 9th International Conference on Learning Representations, 2021
Proceedings of the Conference on Learning Theory, 2021
2020
Direction Matters: On the Implicit Regularization Effect of Stochastic Gradient Descent with Moderate Learning Rate.
CoRR, 2020
Proceedings of the 8th International Conference on Learning Representations, 2020
Proceedings of the 8th International Conference on Learning Representations, 2020
Two-dimensional Intensity Distribution and Connectivity in Ultraviolet Ad-Hoc Network.
Proceedings of the 2020 IEEE International Conference on Communications, 2020
2019
Characterization on Practical Photon Counting Receiver in Optical Scattering Communication.
IEEE Trans. Commun., 2019
Signal Characterization and Achievable Transmission Rate of VLC Under Receiver Nonlinearity.
IEEE Access, 2019
Layer-Dependent Importance Sampling for Training Deep and Large Graph Convolutional Networks.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019
Stochastic Gradient Hamiltonian Monte Carlo Methods with Recursive Variance Reduction.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019
Sampling from Non-Log-Concave Distributions via Variance-Reduced Gradient Langevin Dynamics.
Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics, 2019
2018
Signal Detection Under Short-Interval Sampling of Continuous Waveforms for Optical Wireless Scattering Communication.
IEEE Trans. Wirel. Commun., 2018
IEEE Trans. Commun., 2018
CoRR, 2018
Proceedings of the Thirty-Fourth Conference on Uncertainty in Artificial Intelligence, 2018
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018
Proceedings of the 35th International Conference on Machine Learning, 2018
2017
Saving Gradient and Negative Curvature Computations: Finding Local Minima More Efficiently.
CoRR, 2017
CoRR, 2017
2016
Turbulence channel modeling and non-parametric estimation for optical wireless scattering communication.
Proceedings of the 2016 IEEE International Conference on Communication Systems, 2016
Performance of non-line-of-sight ultraviolet scattering communication under different altitudes.
Proceedings of the 2016 IEEE/CIC International Conference on Communications in China, 2016
Optical wireless scattering communication system with a non-ideal photon-counting receiver.
Proceedings of the 2016 IEEE Global Conference on Signal and Information Processing, 2016
2014
Proceedings of the 48th Asilomar Conference on Signals, Systems and Computers, 2014