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Shiwei Liu
Shiwei Liu
University of Oxford & Eindhoven University of Technology
Bestätigte E-Mail-Adresse bei tue.nl - Startseite
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Zitiert von
Zitiert von
Jahr
More convnets in the 2020s: Scaling up kernels beyond 51x51 using sparsity
S Liu, T Chen, X Chen, X Chen, Q Xiao, B Wu, M Pechenizkiy, D Mocanu, ...
ICLR2023, The International Conference on Learning Representations, 2023
1112023
Do we actually need dense over-parameterization? in-time over-parameterization in sparse training
S Liu, L Yin, DC Mocanu, M Pechenizkiy
ICML2021, International Conference on Machine Learning, 2021
1042021
Sparse Training via Boosting Pruning Plasticity with Neuroregeneration
S Liu, T Chen, X Chen, Z Atashgahi, L Yin, H Kou, L Shen, M Pechenizkiy, ...
NeurIPS2021, Advances in Neural Information Processing Systems, 2021
1012021
Sparse evolutionary deep learning with over one million artificial neurons on commodity hardware
S Liu, DC Mocanu, ARR Matavalam, Y Pei, M Pechenizkiy
Neural Computing and Applications 33, 2589-2604, 2021
872021
The unreasonable effectiveness of random pruning: Return of the most naive baseline for sparse training
S Liu, T Chen, X Chen, L Shen, DC Mocanu, Z Wang, M Pechenizkiy
ICLR2022, The International Conference on Learning Representations, 2022
842022
Selfish sparse RNN training
S Liu, DC Mocanu, Y Pei, M Pechenizkiy
ICML2021, International Conference on Machine Learning, 2021
51*2021
Deep Ensembling with No Overhead for either Training or Testing: The All-Round Blessings of Dynamic Sparsity
S Liu, T Chen, Z Atashgahi, X Chen, G Sokar, E Mocanu, M Pechenizkiy, ...
ICLR2022, The International Conference on Learning Representations, 2021
452021
Topological Insights into Sparse Neural Networks
S Liu, T Van der Lee, A Yaman, Z Atashgahi, D Ferraro, G Sokar, ...
ECML2020, European Conference on Machine Learning, 2020
322020
Efficient and effective training of sparse recurrent neural networks
S Liu, I Ni’mah, V Menkovski, DC Mocanu, M Pechenizkiy
Neural Computing and Applications 33, 9625-9636, 2021
302021
Achieving personalized federated learning with sparse local models
T Huang, S Liu, L Shen, F He, W Lin, D Tao
arXiv preprint arXiv:2201.11380, 2022
232022
A Brain-inspired Algorithm for Training Highly Sparse Neural Networks
Z Atashgahi, J Pieterse, S Liu, DC Mocanu, R Veldhuis, M Pechenizkiy
Machine Learning Journal (ECML-PKDD 2022 journal track), 2019
21*2019
Sparse MoE as the New Dropout: Scaling Dense and Self-Slimmable Transformers
T Chen, Z Zhang, A Jaiswal, S Liu, Z Wang
ICLR2023, The International Conference on Learning Representations, 2023
202023
Sparsity May Cry: Let Us Fail (Current) Sparse Neural Networks Together!
S Liu, T Chen, Z Zhang, X Chen, T Huang, A Jaiswal, Z Wang
ICLR2023, The International Conference on Learning Representations, 2023
192023
Revisiting pruning at initialization through the lens of Ramanujan graph
DNM Hoang, S Liu, R Marculescu, Z Wang
ICLR2023, The International Conference on Learning Representations, 2023
182023
Ten lessons we have learned in the new" sparseland": A short handbook for sparse neural network researchers
S Liu, Z Wang
arXiv preprint arXiv:2302.02596, 2023
152023
Dynamic Sparse Network for Time Series Classification: Learning What to “See”
Q Xiao, B Wu, Y Zhang, S Liu, M Pechenizkiy, E Mocanu, DC Mocanu
NeurIPS2022, 36th Annual Conference on Neural Information Processing Systems, 2022
142022
The Emergence of Essential Sparsity in Large Pre-trained Models: The Weights that Matter
A Jaiswal, S Liu, T Chen, Z Wang
NeurIPS2023, 37th Annual Conference on Neural Information Processing Systems, 2023
132023
Instant Soup: Cheap Pruning Ensembles in A Single Pass Can Draw Lottery Tickets from Large Models
AK JAISWAL, S Liu, T Chen, Y Ding, Z Wang
ICML2023, International Conference on Machine Learning, 2023
112023
You Can Have Better Graph Neural Networks by Not Training Weights at All: Finding Untrained GNNs Tickets
T Huang, T Chen, M Fang, V Menkovski, J Zhao, L Yin, Y Pei, DC Mocanu, ...
LoG 2022, Learning on Graphs Conference (Best Paper Award), 2022
112022
On improving deep learning generalization with adaptive sparse connectivity
S Liu, DC Mocanu, M Pechenizkiy
ICML 2019 workshop of Understanding and Improving Generalization in Deep …, 2019
92019
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