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Jingling Li
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Jaar
How neural networks extrapolate: From feedforward to graph neural networks
K Xu, M Zhang, J Li, SS Du, K Kawarabayashi, S Jegelka
arXiv preprint arXiv:2009.11848, 2020
2942020
What Can Neural Networks Reason About?
K Xu, J Li, M Zhang, SS Du, K Kawarabayashi, S Jegelka
https://arxiv.org/pdf/1905.13211.pdf, 2019
2532019
Tensorized spectrum preserving compression for neural networks
J Su, J Li, B Bhattacharjee, F Huang
arXiv preprint arXiv:1805.10352, 2018
32*2018
How Does a Neural Network’s Architecture Impact Its Robustness to Noisy Labels?
J Li, M Zhang, K Xu, JP Dickerson, J Ba
Advances in Neural Information Processing Systems (2021) 34, 9788-9803, 2020
29*2020
Understanding generalization in deep learning via tensor methods
J Li, Y Sun, J Su, T Suzuki, F Huang
International Conference on Artificial Intelligence and Statistics, 504-515, 2020
282020
Select and permute: An improved online framework for scheduling to minimize weighted completion time
S Khuller, J Li, P Sturmfels, K Sun, P Venkat
Theoretical Computer Science 795, 420-431, 2019
202019
VQ-GNN: A universal framework to scale up graph neural networks using vector quantization
M Ding, K Kong, J Li, C Zhu, J Dickerson, F Huang, T Goldstein
Advances in Neural Information Processing Systems 34, 6733-6746, 2021
172021
Hindsight learning for mdps with exogenous inputs
SR Sinclair, FV Frujeri, CA Cheng, L Marshall, HDO Barbalho, J Li, ...
International Conference on Machine Learning, 31877-31914, 2023
102023
Compact neural architecture designs by tensor representations
J Su, J Li, X Liu, T Ranadive, C Coley, TC Tuan, F Huang
Frontiers in artificial intelligence 5, 728761, 2022
62022
Steering LLMs Towards Unbiased Responses: A Causality-Guided Debiasing Framework
J Li, Z Tang, X Liu, P Spirtes, K Zhang, L Leqi, Y Liu
arXiv preprint arXiv:2403.08743, 2024
12024
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Artikelen 1–10