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2020 – today
- 2024
[j5]Hongchang Zhang
, Kang Yang, Heng Liu, Jiali Hu, Yao Shu, Juan Zeng:
Small-Scale Pedestrian Detection Using Fusion Network and Probabilistic Loss. IEEE Access 12: 42509-42520 (2024)- [c17]Xinyi Xu, Zhaoxuan Wu, Rui Qiao, Arun Verma, Yao Shu, Jingtan Wang, Xinyuan Niu, Zhenfeng He, Jiangwei Chen, Zijian Zhou, Gregory Kang Ruey Lau, Hieu Dao, Lucas Agussurja, Rachael Hwee Ling Sim, Xiaoqiang Lin, Wenyang Hu, Zhongxiang Dai, Pang Wei Koh, Bryan Kian Hsiang Low:
Position Paper: Data-Centric AI in the Age of Large Language Models. EMNLP (Findings) 2024: 11895-11913 - [c16]Zhenfeng He, Yao Shu, Zhongxiang Dai, Bryan Kian Hsiang Low:
Robustifying and Boosting Training-Free Neural Architecture Search. ICLR 2024 - [c15]Xiaoqiang Lin, Zhaoxuan Wu, Zhongxiang Dai, Wenyang Hu, Yao Shu, See-Kiong Ng, Patrick Jaillet, Bryan Kian Hsiang Low:
Use Your INSTINCT: INSTruction optimization for LLMs usIng Neural bandits Coupled with Transformers. ICML 2024 - [i20]Yao Shu, Jiongfeng Fang, Ying Tiffany He, Fei Richard Yu:
OptEx: Expediting First-Order Optimization with Approximately Parallelized Iterations. CoRR abs/2402.11427 (2024) - [i19]Wenyang Hu, Yao Shu, Zongmin Yu, Zhaoxuan Wu, Xiangqiang Lin, Zhongxiang Dai, See-Kiong Ng, Bryan Kian Hsiang Low:
Localized Zeroth-Order Prompt Optimization. CoRR abs/2403.02993 (2024) - [i18]Zhenfeng He, Yao Shu, Zhongxiang Dai, Bryan Kian Hsiang Low:
Robustifying and Boosting Training-Free Neural Architecture Search. CoRR abs/2403.07591 (2024) - [i17]Zhaoxuan Wu, Xiaoqiang Lin, Zhongxiang Dai, Wenyang Hu, Yao Shu, See-Kiong Ng, Patrick Jaillet, Bryan Kian Hsiang Low:
Prompt Optimization with EASE? Efficient Ordering-aware Automated Selection of Exemplars. CoRR abs/2405.16122 (2024) - [i16]Xinyi Xu, Zhaoxuan Wu, Rui Qiao, Arun Verma, Yao Shu, Jingtan Wang, Xinyuan Niu, Zhenfeng He, Jiangwei Chen, Zijian Zhou, Gregory Kang Ruey Lau, Hieu Dao, Lucas Agussurja, Rachael Hwee Ling Sim, Xiaoqiang Lin, Wenyang Hu, Zhongxiang Dai, Pang Wei Koh, Bryan Kian Hsiang Low:
Data-Centric AI in the Age of Large Language Models. CoRR abs/2406.14473 (2024) - [i15]Chenxing Wei, Yao Shu, Ying Tiffany He, Fei Richard Yu:
Flexora: Flexible Low Rank Adaptation for Large Language Models. CoRR abs/2408.10774 (2024) - [i14]Yao Shu, Wenyang Hu, See-Kiong Ng, Bryan Kian Hsiang Low, Fei Richard Yu:
Ferret: Federated Full-Parameter Tuning at Scale for Large Language Models. CoRR abs/2409.06277 (2024) - 2023
- [c14]Zhongxiang Dai, Yao Shu, Arun Verma, Flint Xiaofeng Fan, Bryan Kian Hsiang Low, Patrick Jaillet:
Federated Neural Bandits. ICLR 2023 - [c13]Yao Shu, Zhongxiang Dai, Weicong Sng, Arun Verma, Patrick Jaillet, Bryan Kian Hsiang Low:
Zeroth-Order Optimization with Trajectory-Informed Derivative Estimation. ICLR 2023 - [c12]Zhongxiang Dai, Gregory Kang Ruey Lau, Arun Verma, Yao Shu, Bryan Kian Hsiang Low, Patrick Jaillet:
Quantum Bayesian Optimization. NeurIPS 2023 - [c11]Arun Verma, Zhongxiang Dai, Yao Shu, Bryan Kian Hsiang Low:
Exploiting Correlated Auxiliary Feedback in Parameterized Bandits. NeurIPS 2023 - [i13]Yao Shu, Xiaoqiang Lin, Zhongxiang Dai, Bryan Kian Hsiang Low:
Federated Zeroth-Order Optimization using Trajectory-Informed Surrogate Gradients. CoRR abs/2308.04077 (2023) - [i12]Xiaoqiang Lin, Zhaoxuan Wu, Zhongxiang Dai, Wenyang Hu, Yao Shu, See-Kiong Ng, Patrick Jaillet, Bryan Kian Hsiang Low:
Use Your INSTINCT: INSTruction optimization usIng Neural bandits Coupled with Transformers. CoRR abs/2310.02905 (2023) - [i11]Zhongxiang Dai, Gregory Kang Ruey Lau, Arun Verma, Yao Shu, Bryan Kian Hsiang Low, Patrick Jaillet:
Quantum Bayesian Optimization. CoRR abs/2310.05373 (2023) - [i10]Arun Verma, Zhongxiang Dai, Yao Shu, Bryan Kian Hsiang Low:
Exploiting Correlated Auxiliary Feedback in Parameterized Bandits. CoRR abs/2311.02715 (2023) - 2022
- [c10]Yao Shu, Shaofeng Cai, Zhongxiang Dai, Beng Chin Ooi, Bryan Kian Hsiang Low:
NASI: Label- and Data-agnostic Neural Architecture Search at Initialization. ICLR 2022 - [c9]Zhaoxuan Wu, Yao Shu, Bryan Kian Hsiang Low:
DAVINZ: Data Valuation using Deep Neural Networks at Initialization. ICML 2022: 24150-24176 - [c8]Zhongxiang Dai, Yao Shu, Bryan Kian Hsiang Low, Patrick Jaillet:
Sample-Then-Optimize Batch Neural Thompson Sampling. NeurIPS 2022 - [c7]Yao Shu, Zhongxiang Dai, Zhaoxuan Wu, Bryan Kian Hsiang Low:
Unifying and Boosting Gradient-Based Training-Free Neural Architecture Search. NeurIPS 2022 - [c6]Yao Shu, Yizhou Chen, Zhongxiang Dai, Bryan Kian Hsiang Low:
Neural ensemble search via Bayesian sampling. UAI 2022: 1803-1812 - [i9]Yao Shu, Zhongxiang Dai, Zhaoxuan Wu, Bryan Kian Hsiang Low:
Unifying and Boosting Gradient-Based Training-Free Neural Architecture Search. CoRR abs/2201.09785 (2022) - [i8]Zhongxiang Dai, Yao Shu, Arun Verma, Flint Xiaofeng Fan, Bryan Kian Hsiang Low, Patrick Jaillet:
Federated Neural Bandit. CoRR abs/2205.14309 (2022) - [i7]Zhongxiang Dai, Yao Shu, Bryan Kian Hsiang Low, Patrick Jaillet:
Sample-Then-Optimize Batch Neural Thompson Sampling. CoRR abs/2210.06850 (2022) - 2021
- [c5]Shaofeng Cai, Yao Shu, Wei Wang:
Dynamic Routing Networks. WACV 2021: 3587-3596 - [i6]Yao Shu, Shaofeng Cai, Zhongxiang Dai, Beng Chin Ooi, Bryan Kian Hsiang Low:
NASI: Label- and Data-agnostic Neural Architecture Search at Initialization. CoRR abs/2109.00817 (2021) - [i5]Yao Shu, Yizhou Chen, Zhongxiang Dai, Bryan Kian Hsiang Low:
Going Beyond Neural Architecture Search with Sampling-based Neural Ensemble Search. CoRR abs/2109.02533 (2021) - 2020
- [j4]Yao Shu, Heng Zhang:
Multimodal information fusion based human movement recognition. Multim. Tools Appl. 79(7-8): 5043-5052 (2020) - [c4]Yao Shu, Wei Wang, Shaofeng Cai:
Understanding Architectures Learnt by Cell-based Neural Architecture Search. ICLR 2020 - [i4]Min Zhang, Yao Shu, Kun He:
Tight Lower Complexity Bounds for Strongly Convex Finite-Sum Optimization. CoRR abs/2010.08766 (2020)
2010 – 2019
- 2019
- [j3]Chenglei Zhang, Buyun Sheng, Xiyan Yin, Feiyu Zhao, Yao Shu:
Research and development of off-line services for the 3D automatic printing machine based on cloud manufacturing. J. Ambient Intell. Humaniz. Comput. 10(3): 1109-1128 (2019) - [j2]Buyun Sheng, Feiyu Zhao, Chenglei Zhang, Xiyan Yin, Yao Shu:
Parameterized representation and solution method of the lightweight 3D model virtual assembly constraint. J. Ambient Intell. Humaniz. Comput. 10(3): 1167-1187 (2019) - [j1]Heng Zhang, Jan D. Smeddinck, Rainer Malaka, Yao Shu, Chong Chen, Bo He, Zengjun Fu, Michael Lawo:
Wireless non-invasive motion tracking of functional behavior. Pervasive Mob. Comput. 54: 29-44 (2019) - [i3]Junzhe Zhang, Sai-Ho Yeung, Yao Shu, Bingsheng He, Wei Wang:
Efficient Memory Management for GPU-based Deep Learning Systems. CoRR abs/1903.06631 (2019) - [i2]Shaofeng Cai, Yao Shu, Wei Wang, Beng Chin Ooi:
ISBNet: Instance-aware Selective Branching Network. CoRR abs/1905.04849 (2019) - 2018
- [c3]Chong Chen, Yao Shu, Kuang-I Shu, Heng Zhang:
WiTT: Modeling and the evaluation of table tennis actions based on WIFI signals. ICPR 2018: 3100-3107 - [c2]Yao Shu, Chong Chen, Kuang-I Shu, Heng Zhang:
Research on Human Motion Recognition Based on Wi-Fi and Inertial Sensor Signal Fusion. SmartWorld/SCALCOM/UIC/ATC/CBDCom/IOP/SCI 2018: 496-504 - 2017
- [i1]Yao Shu, Man Zhu, Kun He, John E. Hopcroft, Pan Zhou:
Understanding Deep Representations through Random Weights. CoRR abs/1704.00330 (2017)
2000 – 2009
- 2005
- [c1]Jianxing Li, XinJun Mao, Yao Shu:
An OO-based Design Model of Software Agent. PDCAT 2005: 434-440
Coauthor Index
aka: Bryan Kian Hsiang Low
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