Zhongxiang Dai

According to our database, Zhongxiang Dai authored at least 37 papers between 2015 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Robustifying and Boosting Training-Free Neural Architecture Search.

Zhenfeng He, Yao Shu, Zhongxiang Dai, Bryan Kian Hsiang Low

CoRR, 2024

Localized Zeroth-Order Prompt Optimization.

Wenyang Hu, Yao Shu, Zongmin Yu, Zhaoxuan Wu, Xiangqiang Lin, Zhongxiang Dai, See-Kiong Ng, Bryan Kian Hsiang Low

CoRR, 2024

2023

Use Your INSTINCT: INSTruction optimization usIng Neural bandits Coupled with Transformers.

Xiaoqiang Lin, Zhaoxuan Wu, Zhongxiang Dai, Wenyang Hu, Yao Shu, See-Kiong Ng, Patrick Jaillet, Bryan Kian Hsiang Low

CoRR, 2023

WASA: WAtermark-based Source Attribution for Large Language Model-Generated Data.

Jingtan Wang, Xinyang Lu, Zitong Zhao, Zhongxiang Dai, Chuan-Sheng Foo, See-Kiong Ng, Bryan Kian Hsiang Low

CoRR, 2023

Federated Zeroth-Order Optimization using Trajectory-Informed Surrogate Gradients.

Yao Shu, Xiaoqiang Lin, Zhongxiang Dai, Bryan Kian Hsiang Low

CoRR, 2023

FedHQL: Federated Heterogeneous Q-Learning.

Flint Xiaofeng Fan, Yining Ma, Zhongxiang Dai, Cheston Tan, Bryan Kian Hsiang Low, Roger Wattenhofer

CoRR, 2023

Recursive reasoning-based training-time adversarial machine learning.

Yizhou Chen, Zhongxiang Dai, Haibin Yu, Bryan Kian Hsiang Low, Teck-Hua Ho

Artif. Intell., 2023

Exploiting Correlated Auxiliary Feedback in Parameterized Bandits.

Arun Verma, Zhongxiang Dai, Yao Shu, Bryan Kian Hsiang Low

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Batch Bayesian Optimization For Replicable Experimental Design.

Zhongxiang Dai, Quoc Phong Nguyen, Sebastian Tay, Daisuke Urano, Richalynn Leong, Bryan Kian Hsiang Low, Patrick Jaillet

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Quantum Bayesian Optimization.

Zhongxiang Dai, Gregory Kang Ruey Lau, Arun Verma, Yao Shu, Bryan Kian Hsiang Low, Patrick Jaillet

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Training-Free Neural Active Learning with Initialization-Robustness Guarantees.

Apivich Hemachandra, Zhongxiang Dai, Jasraj Singh, See-Kiong Ng, Bryan Kian Hsiang Low

Proceedings of the International Conference on Machine Learning, 2023

Zeroth-Order Optimization with Trajectory-Informed Derivative Estimation.

Yao Shu, Zhongxiang Dai, Weicong Sng, Arun Verma, Patrick Jaillet, Bryan Kian Hsiang Low

Proceedings of the Eleventh International Conference on Learning Representations, 2023

Federated Neural Bandits.

Zhongxiang Dai, Yao Shu, Arun Verma, Flint Xiaofeng Fan, Bryan Kian Hsiang Low, Patrick Jaillet

Proceedings of the Eleventh International Conference on Learning Representations, 2023

FedHQL: Federated Heterogeneous Q-Learning.

Flint Xiaofeng Fan, Yining Ma, Zhongxiang Dai, Cheston Tan, Bryan Kian Hsiang Low

Proceedings of the 2023 International Conference on Autonomous Agents and Multiagent Systems, 2023

2022

Federated Neural Bandit.

Zhongxiang Dai, Yao Shu, Arun Verma, Flint Xiaofeng Fan, Bryan Kian Hsiang Low, Patrick Jaillet

CoRR, 2022

Adjusted Expected Improvement for Cumulative Regret Minimization in Noisy Bayesian Optimization.

Shouri Hu, Haowei Wang, Zhongxiang Dai, Bryan Kian Hsiang Low, Szu Hui Ng

CoRR, 2022

Neural ensemble search via Bayesian sampling.

Yao Shu, Yizhou Chen, Zhongxiang Dai, Bryan Kian Hsiang Low

Proceedings of the Uncertainty in Artificial Intelligence, 2022

On provably robust meta-Bayesian optimization.

Zhongxiang Dai, Yizhou Chen, Haibin Yu, Bryan Kian Hsiang Low, Patrick Jaillet

Proceedings of the Uncertainty in Artificial Intelligence, 2022

Unifying and Boosting Gradient-Based Training-Free Neural Architecture Search.

Yao Shu, Zhongxiang Dai, Zhaoxuan Wu, Bryan Kian Hsiang Low

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Sample-Then-Optimize Batch Neural Thompson Sampling.

Zhongxiang Dai, Yao Shu, Bryan Kian Hsiang Low, Patrick Jaillet

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Bayesian Optimization under Stochastic Delayed Feedback.

Arun Verma, Zhongxiang Dai, Bryan Kian Hsiang Low

Proceedings of the International Conference on Machine Learning, 2022

NASI: Label- and Data-agnostic Neural Architecture Search at Initialization.

Yao Shu, Shaofeng Cai, Zhongxiang Dai, Beng Chin Ooi, Bryan Kian Hsiang Low

Proceedings of the Tenth International Conference on Learning Representations, 2022

2021

Going Beyond Neural Architecture Search with Sampling-based Neural Ensemble Search.

Yao Shu, Yizhou Chen, Zhongxiang Dai, Bryan Kian Hsiang Low

CoRR, 2021

Optimizing Conditional Value-At-Risk of Black-Box Functions.

Quoc Phong Nguyen, Zhongxiang Dai, Bryan Kian Hsiang Low, Patrick Jaillet

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Fault-Tolerant Federated Reinforcement Learning with Theoretical Guarantee.

Flint Xiaofeng Fan, Yining Ma, Zhongxiang Dai, Wei Jing, Cheston Tan, Bryan Kian Hsiang Low

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Differentially Private Federated Bayesian Optimization with Distributed Exploration.

Zhongxiang Dai, Bryan Kian Hsiang Low, Patrick Jaillet

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Value-at-Risk Optimization with Gaussian Processes.

Quoc Phong Nguyen, Zhongxiang Dai, Bryan Kian Hsiang Low, Patrick Jaillet

Proceedings of the 38th International Conference on Machine Learning, 2021

2020

Federated Bayesian Optimization via Thompson Sampling.

Zhongxiang Dai, Bryan Kian Hsiang Low, Patrick Jaillet

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Private Outsourced Bayesian Optimization.

Dmitrii Kharkovskii, Zhongxiang Dai, Bryan Kian Hsiang Low

Proceedings of the 37th International Conference on Machine Learning, 2020

R2-B2: Recursive Reasoning-Based Bayesian Optimization for No-Regret Learning in Games.

Zhongxiang Dai, Yizhou Chen, Bryan Kian Hsiang Low, Patrick Jaillet, Teck-Hua Ho

Proceedings of the 37th International Conference on Machine Learning, 2020

2019

Bayesian Optimization with Binary Auxiliary Information.

Yehong Zhang, Zhongxiang Dai, Bryan Kian Hsiang Low

Proceedings of the Thirty-Fifth Conference on Uncertainty in Artificial Intelligence, 2019

Implicit Posterior Variational Inference for Deep Gaussian Processes.

Haibin Yu, Yizhou Chen, Bryan Kian Hsiang Low, Patrick Jaillet, Zhongxiang Dai

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Bayesian Optimization Meets Bayesian Optimal Stopping.

Zhongxiang Dai, Haibin Yu, Bryan Kian Hsiang Low, Patrick Jaillet

Proceedings of the 36th International Conference on Machine Learning, 2019

2017

The effects of a mid-task break on the brain connectome in healthy participants: A resting-state functional MRI study.

Yu Sun, Julian Lim, Zhongxiang Dai, Kianfoong Wong, Fumihiko Taya, Yu Chen, Junhua Li, Nitish V. Thakor, Anastasios Bezerianos

NeuroImage, 2017

Identification of gait-related brain activity using electroencephalographic signals.

Jingwen Chai, Gong Chen, Pavithra Thangavel, Georgios N. Dimitrakopoulos, Ioannis Kakkos, Yu Sun, Zhongxiang Dai, Haoyong Yu, Nitish V. Thakor, Anastasios Bezerianos, Junhua Li

Proceedings of the 8th International IEEE/EMBS Conference on Neural Engineering, 2017

Connectome pattern alterations with increment of mental fatigue in one-hour driving simulation.

Bing Liang Chua, Zhongxiang Dai, Nitish V. Thakor, Anastasios Bezerianos, Yu Sun

Proceedings of the 2017 39th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), 2017

2015

Cognitive Workload Discrimination in Flight Simulation Task Using a Generalized Measure of Association.

Zhongxiang Dai, José C. Príncipe, Anastasios Bezerianos, Nitish V. Thakor

Proceedings of the Neural Information Processing - 22nd International Conference, 2015