Difan Zou

According to our database1, Difan Zou authored at least 24 papers between 2014 and 2020.

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Bibliography

2020
Gradient descent optimizes over-parameterized deep ReLU networks.
Mach. Learn., 2020

On the Global Convergence of Training Deep Linear ResNets.
Proceedings of the 8th International Conference on Learning Representations, 2020

Improving Adversarial Robustness Requires Revisiting Misclassified Examples.
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

How Much Over-parameterization Is Sufficient to Learn Deep ReLU Networks?
CoRR, 2019

Laplacian Smoothing Stochastic Gradient Markov Chain Monte Carlo.
CoRR, 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

An Improved Analysis of Training Over-parameterized Deep Neural Networks.
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

Secrecy Rate of MISO Optical Wireless Scattering Communications.
IEEE Trans. Commun., 2018

Stochastic Gradient Descent Optimizes Over-parameterized Deep ReLU Networks.
CoRR, 2018

Subsampled Stochastic Variance-Reduced Gradient Langevin Dynamics.
Proceedings of the Thirty-Fourth Conference on Uncertainty in Artificial Intelligence, 2018

Global Convergence of Langevin Dynamics Based Algorithms for Nonconvex Optimization.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Stochastic Variance-Reduced Hamilton Monte Carlo Methods.
Proceedings of the 35th International Conference on Machine Learning, 2018

2017
Saving Gradient and Negative Curvature Computations: Finding Local Minima More Efficiently.
CoRR, 2017

Analysis on Practical Photon Counting Receiver in Optical Scattering Communication.
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
Improving the NLOS optical scattering channel via beam reshaping.
Proceedings of the 48th Asilomar Conference on Signals, Systems and Computers, 2014


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