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Yao Shu
Yao Shu
Guangdong Lab of AI and Digital Economy (SZ)
Verified email at gml.ac.cn - Homepage
Title
Cited by
Cited by
Year
Understanding architectures learnt by cell-based neural architecture search
Y Shu, W Wang, S Cai
Proceedings of the 8th International Conference on Learning Representations …, 2020
1042020
Effective and efficient dropout for deep convolutional neural networks
S Cai, Y Shu, G Chen, BC Ooi, W Wang, M Zhang
arXiv preprint arXiv:1904.03392, 2019
812019
Efficient memory management for gpu-based deep learning systems
J Zhang, SH Yeung, Y Shu, B He, W Wang
arXiv preprint arXiv:1903.06631, 2019
492019
DAVINZ: Data Valuation using Deep Neural Networks at Initialization
Z Wu, Y Shu, BKH Low
Proceedings of the 39th International Conference on Machine Learning (ICML-22), 2022
442022
NASI: Label- and Data-agnostic Neural Architecture Search at Initialization
Y Shu, S Cai, Z Dai, BC Ooi, BKH Low
Proceedings of the 10th International Conference on Learning Representations …, 2022
442022
Dynamic routing networks
S Cai, Y Shu, W Wang
Proceedings of the IEEE/CVF winter conference on applications of computer …, 2021
432021
Unifying and Boosting Gradient-Based Training-Free Neural Architecture Search
Y Shu, Z Dai, Z Wu, BKH Low
Proceedings of the 36th Conference on Neural Information Processing Systems …, 2022
262022
Federated Neural Bandit
Z Dai, Y Shu, A Verma, FX Fan, BKH Low, P Jaillet
Proceedings of the 11th International Conference on Learning Representations …, 2022
202022
Sample-Then-Optimize Batch Neural Thompson Sampling
Z Dai, Y Shu, BKH Low, P Jaillet
Proceedings of the 36th Conference on Neural Information Processing Systems …, 2022
152022
Neural Ensemble Search via Bayesian Sampling
Y Shu, Y CHEN, Z Dai, BKH Low
Proceedings of the 38th Conference on Uncertainty in Artificial Intelligence …, 2022
11*2022
Use Your INSTINCT: INSTruction optimization usIng Neural bandits Coupled with Transformers
X Lin, Z Wu, Z Dai, W Hu, Y Shu, SK Ng, P Jaillet, BKH Low
Proceedings of the 41st International Conference on Machine Learning (ICML-24), 2024
72024
Zeroth-order optimization with trajectory-informed derivative estimation
Y Shu, Z Dai, W Sng, A Verma, P Jaillet, BKH Low
Proceedings of the 11th International Conference on Learning Representations …, 2022
72022
Randomness in Deconvolutional Networks for Visual Representation
K He, J Wang, H Li, Y Shu, M Zhang, M Zhu, L Wang, JE Hopcroft
arXiv preprint arXiv:1704.00330, 2017
7*2017
Federated Zeroth-Order Optimization using Trajectory-Informed Surrogate Gradients
Y Shu, X Lin, Z Dai, BKH Low
arXiv preprint arXiv:2308.04077, 2023
42023
Quantum Bayesian Optimization
Z Dai, GKR Lau, A Verma, Y Shu, BKH Low, P Jaillet
Proceedings of the 37th Conference on Neural Information Processing Systems …, 2023
32023
Localized zeroth-order prompt optimization
W Hu, Y Shu, Z Yu, Z Wu, X Lin, Z Dai, SK Ng, BKH Low
arXiv preprint arXiv:2403.02993, 2024
22024
Prompt Optimization with EASE? Efficient Ordering-aware Automated Selection of Exemplars
Z Wu, X Lin, Z Dai, W Hu, Y Shu, SK Ng, P Jaillet, BKH Low
arXiv preprint arXiv:2405.16122, 2024
2024
OptEx: Expediting First-Order Optimization with Approximately Parallelized Iterations
Y Shu, J Fang, YT He, FR Yu
arXiv preprint arXiv:2402.11427, 2024
2024
Data valuation in federated learning
Z Wu, X Xu, RHL Sim, Y Shu, X Lin, L Agussurja, Z Dai, SK Ng, CS Foo, ...
Federated Learning, 281-296, 2024
2024
Exploiting Correlated Auxiliary Feedback in Parameterized Bandits
A Verma, Z Dai, Y Shu, BKH Low
Proceedings of the 37th Conference on Neural Information Processing Systems …, 2023
2023
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