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Zhongxiang Dai
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2020 – today
- 2024
- [c29]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 - [c28]Zhenfeng He, Yao Shu, Zhongxiang Dai, Bryan Kian Hsiang Low:
Robustifying and Boosting Training-Free Neural Architecture Search. ICLR 2024 - [c27]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 - [i30]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) - [i29]Zhenfeng He, Yao Shu, Zhongxiang Dai, Bryan Kian Hsiang Low:
Robustifying and Boosting Training-Free Neural Architecture Search. CoRR abs/2403.07591 (2024) - [i28]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) - [i27]Xiaoqiang Lin, Zhongxiang Dai, Arun Verma, See-Kiong Ng, Patrick Jaillet, Bryan Kian Hsiang Low:
Prompt Optimization with Human Feedback. CoRR abs/2405.17346 (2024) - [i26]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) - [i25]Arun Verma, Zhongxiang Dai, Xiaoqiang Lin, Patrick Jaillet, Bryan Kian Hsiang Low:
Neural Dueling Bandits. CoRR abs/2407.17112 (2024) - 2023
- [j2]Yizhou Chen, Zhongxiang Dai, Haibin Yu, Bryan Kian Hsiang Low
, Teck-Hua Ho:
Recursive reasoning-based training-time adversarial machine learning. Artif. Intell. 315: 103837 (2023) - [c26]Flint Xiaofeng Fan, Yining Ma, Zhongxiang Dai, Cheston Tan, Bryan Kian Hsiang Low:
FedHQL: Federated Heterogeneous Q-Learning. AAMAS 2023: 2810-2812 - [c25]Zhongxiang Dai, Yao Shu, Arun Verma, Flint Xiaofeng Fan, Bryan Kian Hsiang Low, Patrick Jaillet:
Federated Neural Bandits. ICLR 2023 - [c24]Yao Shu, Zhongxiang Dai, Weicong Sng, Arun Verma, Patrick Jaillet, Bryan Kian Hsiang Low:
Zeroth-Order Optimization with Trajectory-Informed Derivative Estimation. ICLR 2023 - [c23]Apivich Hemachandra, Zhongxiang Dai, Jasraj Singh, See-Kiong Ng, Bryan Kian Hsiang Low:
Training-Free Neural Active Learning with Initialization-Robustness Guarantees. ICML 2023: 12931-12971 - [c22]Zhongxiang Dai, Gregory Kang Ruey Lau, Arun Verma, Yao Shu, Bryan Kian Hsiang Low, Patrick Jaillet:
Quantum Bayesian Optimization. NeurIPS 2023 - [c21]Zhongxiang Dai, Quoc Phong Nguyen, Sebastian Tay, Daisuke Urano, Richalynn Leong, Bryan Kian Hsiang Low, Patrick Jaillet:
Batch Bayesian Optimization For Replicable Experimental Design. NeurIPS 2023 - [c20]Arun Verma, Zhongxiang Dai, Yao Shu, Bryan Kian Hsiang Low:
Exploiting Correlated Auxiliary Feedback in Parameterized Bandits. NeurIPS 2023 - [i24]Flint Xiaofeng Fan, Yining Ma, Zhongxiang Dai, Cheston Tan
FedHQL: Federated Heterogeneous Q-Learning. CoRR abs/2301.11135 (2023) - [i23]Apivich Hemachandra, Zhongxiang Dai, Jasraj Singh, See-Kiong Ng, Bryan Kian Hsiang Low:
Training-Free Neural Active Learning with Initialization-Robustness Guarantees. CoRR abs/2306.04454 (2023) - [i22]Yao Shu, Xiaoqiang Lin, Zhongxiang Dai, Bryan Kian Hsiang Low:
Federated Zeroth-Order Optimization using Trajectory-Informed Surrogate Gradients. CoRR abs/2308.04077 (2023) - [i21]Jingtan Wang, Xinyang Lu, Zitong Zhao, Zhongxiang Dai, Chuan-Sheng Foo, See-Kiong Ng, Bryan Kian Hsiang Low:
WASA: WAtermark-based Source Attribution for Large Language Model-Generated Data. CoRR abs/2310.00646 (2023) - [i20]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) - [i19]Zhongxiang Dai, Gregory Kang Ruey Lau, Arun Verma, Yao Shu, Bryan Kian Hsiang Low, Patrick Jaillet:
Quantum Bayesian Optimization. CoRR abs/2310.05373 (2023) - [i18]Zhongxiang Dai, Quoc Phong Nguyen, Sebastian Shenghong Tay, Daisuke Urano, Richalynn Leong, Bryan Kian Hsiang Low, Patrick Jaillet:
Batch Bayesian Optimization for Replicable Experimental Design. CoRR abs/2311.01195 (2023) - [i17]Arun Verma, Zhongxiang Dai, Yao Shu, Bryan Kian Hsiang Low:
Exploiting Correlated Auxiliary Feedback in Parameterized Bandits. CoRR abs/2311.02715 (2023) - 2022
- [c19]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 - [c18]Arun Verma, Zhongxiang Dai, Bryan Kian Hsiang Low:
Bayesian Optimization under Stochastic Delayed Feedback. ICML 2022: 22145-22167 - [c17]Zhongxiang Dai, Yao Shu, Bryan Kian Hsiang Low, Patrick Jaillet:
Sample-Then-Optimize Batch Neural Thompson Sampling. NeurIPS 2022 - [c16]Yao Shu, Zhongxiang Dai, Zhaoxuan Wu, Bryan Kian Hsiang Low:
Unifying and Boosting Gradient-Based Training-Free Neural Architecture Search. NeurIPS 2022 - [c15]Zhongxiang Dai, Yizhou Chen, Haibin Yu, Bryan Kian Hsiang Low, Patrick Jaillet:
On provably robust meta-Bayesian optimization. UAI 2022: 475-485 - [c14]Yao Shu, Yizhou Chen, Zhongxiang Dai, Bryan Kian Hsiang Low:
Neural ensemble search via Bayesian sampling. UAI 2022: 1803-1812 - [i16]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) - [i15]Shouri Hu, Haowei Wang, Zhongxiang Dai, Bryan Kian Hsiang Low, Szu Hui Ng:
Adjusted Expected Improvement for Cumulative Regret Minimization in Noisy Bayesian Optimization. CoRR abs/2205.04901 (2022) - [i14]Zhongxiang Dai, Yao Shu, Arun Verma, Flint Xiaofeng Fan, Bryan Kian Hsiang Low, Patrick Jaillet:
Federated Neural Bandit. CoRR abs/2205.14309 (2022) - [i13]Zhongxiang Dai, Yizhou Chen, Haibin Yu, Bryan Kian Hsiang Low, Patrick Jaillet:
On Provably Robust Meta-Bayesian Optimization. CoRR abs/2206.06872 (2022) - [i12]Arun Verma, Zhongxiang Dai, Bryan Kian Hsiang Low:
Bayesian Optimization under Stochastic Delayed Feedback. CoRR abs/2206.09341 (2022) - [i11]Zhongxiang Dai, Yao Shu, Bryan Kian Hsiang Low, Patrick Jaillet:
Sample-Then-Optimize Batch Neural Thompson Sampling. CoRR abs/2210.06850 (2022) - 2021
- [c13]Quoc Phong Nguyen, Zhongxiang Dai, Bryan Kian Hsiang Low, Patrick Jaillet:
Value-at-Risk Optimization with Gaussian Processes. ICML 2021: 8063-8072 - [c12]Flint Xiaofeng Fan, Yining Ma, Zhongxiang Dai, Wei Jing, Cheston Tan, Bryan Kian Hsiang Low:
Fault-Tolerant Federated Reinforcement Learning with Theoretical Guarantee. NeurIPS 2021: 1007-1021 - [c11]Quoc Phong Nguyen, Zhongxiang Dai, Bryan Kian Hsiang Low, Patrick Jaillet:
Optimizing Conditional Value-At-Risk of Black-Box Functions. NeurIPS 2021: 4170-4180 - [c10]Zhongxiang Dai, Bryan Kian Hsiang Low, Patrick Jaillet:
Differentially Private Federated Bayesian Optimization with Distributed Exploration. NeurIPS 2021: 9125-9139 - [i10]Quoc Phong Nguyen, Zhongxiang Dai, Bryan Kian Hsiang Low, Patrick Jaillet:
Value-at-Risk Optimization with Gaussian Processes. CoRR abs/2105.06126 (2021) - [i9]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) - [i8]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) - [i7]Flint Xiaofeng Fan, Yining Ma, Zhongxiang Dai, Wei Jing, Cheston Tan, Bryan Kian Hsiang Low:
Fault-Tolerant Federated Reinforcement Learning with Theoretical Guarantee. CoRR abs/2110.14074 (2021) - [i6]Zhongxiang Dai, Bryan Kian Hsiang Low, Patrick Jaillet:
Differentially Private Federated Bayesian Optimization with Distributed Exploration. CoRR abs/2110.14153 (2021) - 2020
- [c9]Zhongxiang Dai, Yizhou Chen, Bryan Kian Hsiang Low, Patrick Jaillet, Teck-Hua Ho:
R2-B2: Recursive Reasoning-Based Bayesian Optimization for No-Regret Learning in Games. ICML 2020: 2291-2301 - [c8]Dmitrii Kharkovskii, Zhongxiang Dai, Bryan Kian Hsiang Low:
Private Outsourced Bayesian Optimization. ICML 2020: 5231-5242 - [c7]Zhongxiang Dai, Bryan Kian Hsiang Low, Patrick Jaillet:
Federated Bayesian Optimization via Thompson Sampling. NeurIPS 2020 - [i5]Zhongxiang Dai, Yizhou Chen, Kian Hsiang Low, Patrick Jaillet, Teck-Hua Ho:
R2-B2: Recursive Reasoning-Based Bayesian Optimization for No-Regret Learning in Games. CoRR abs/2006.16679 (2020) - [i4]Zhongxiang Dai, Kian Hsiang Low, Patrick Jaillet:
Federated Bayesian Optimization via Thompson Sampling. CoRR abs/2010.10154 (2020) - [i3]Dmitrii Kharkovskii, Zhongxiang Dai, Bryan Kian Hsiang Low:
Private Outsourced Bayesian Optimization. CoRR abs/2010.12799 (2020)
2010 – 2019
- 2019
- [c6]Zhongxiang Dai, Haibin Yu, Bryan Kian Hsiang Low, Patrick Jaillet:
Bayesian Optimization Meets Bayesian Optimal Stopping. ICML 2019: 1496-1506 - [c5]Haibin Yu, Yizhou Chen, Bryan Kian Hsiang Low, Patrick Jaillet, Zhongxiang Dai:
Implicit Posterior Variational Inference for Deep Gaussian Processes. NeurIPS 2019: 14475-14486 - [c4]Yehong Zhang, Zhongxiang Dai, Bryan Kian Hsiang Low:
Bayesian Optimization with Binary Auxiliary Information. UAI 2019: 1222-1232 - [i2]Yehong Zhang, Zhongxiang Dai, Kian Hsiang Low:
Bayesian Optimization with Binary Auxiliary Information. CoRR abs/1906.07277 (2019) - [i1]Haibin Yu, Yizhou Chen, Zhongxiang Dai, Kian Hsiang Low, Patrick Jaillet:
Implicit Posterior Variational Inference for Deep Gaussian Processes. CoRR abs/1910.11998 (2019) - 2017
- [j1]Yu Sun
The effects of a mid-task break on the brain connectome in healthy participants: A resting-state functional MRI study. NeuroImage 152: 19-30 (2017) - [c3]Bing Liang Chua, Zhongxiang Dai, Nitish V. Thakor, Anastasios Bezerianos, Yu Sun
Connectome pattern alterations with increment of mental fatigue in one-hour driving simulation. EMBC 2017: 4355-4358 - [c2]Jingwen Chai, Gong Chen, Pavithra Thangavel, Georgios N. Dimitrakopoulos
Identification of gait-related brain activity using electroencephalographic signals. NER 2017: 548-551 - 2015
- [c1]Zhongxiang Dai, José C. Príncipe, Anastasios Bezerianos, Nitish V. Thakor:
Cognitive Workload Discrimination in Flight Simulation Task Using a Generalized Measure of Association. ICONIP (3) 2015: 692-699
Coauthor Index
aka: Bryan Kian Hsiang Low
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last updated on 2024-11-19 20:45 CET by the dblp team
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