Shiyu Liang
Cited by
Cited by
Enhancing the reliability of out-of-distribution image detection in neural networks
S Liang, Y Li, R Srikant
6th International Conference on Learning Representations (ICLR), 2018, 2017
Why deep neural networks for function approximation?
S Liang, R Srikant
5th International Conference on Learning Representations (ICLR), 2017, 2016
Adding One Neuron Can Eliminate All Bad Local Minima
S Liang, R Sun, JD Lee, R Srikant
Thirty-second Conference on Neural Information Processing Systems (NeurIPS …, 2018
Understanding the loss surface of neural networks for binary classification
S Liang, R Sun, Y Li, R Srikant
Thirty-sixth International Conference on Machine Learning (ICML), 2018, 2018
Why deep neural networks
S Liang, R Srikant
arXiv preprint arXiv:1610.04161, 2016
The global landscape of neural networks: An overview
R Sun, D Li, S Liang, T Ding, R Srikant
IEEE Signal Processing Magazine 37 (5), 95-108, 2020
Revisiting landscape analysis in deep neural networks: Eliminating decreasing paths to infinity
S Liang, R Sun, R Srikant
arXiv preprint arXiv:1912.13472, 2019
FINE: A framework for distributed learning on incomplete observations for heterogeneous crowdsensing networks
L Fu, S Ma, L Kong, S Liang, X Wang
IEEE/ACM Transactions on Networking 26 (3), 1092-1109, 2018
The Role of Regularization in Overparameterized Neural Networks*
S Satpathi, H Gupta, S Liang, R Srikant
2020 59th IEEE Conference on Decision and Control (CDC), 4683-4688, 2020
Achieving small test error in mildly overparameterized neural networks
S Liang, R Sun, R Srikant
arXiv preprint arXiv:2104.11895, 2021
The role of explicit regularization in overparameterized neural networks
S Liang
University of Illinois at Urbana-Champaign, 2021
Are we still friends: Kernel multivariate survival analysis
S Liang, R Luo, G Chen, S Ma, W Wu, L Song, X Tian, X Wang
2014 IEEE Global Communications Conference, 405-410, 2014
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