ML Anthology

Dai, Zhongxiang

41 publications

ICLRW 2025 Active Human Feedback Collection via Neural Contextual Dueling Bandits Arun Verma, Xiaoqiang Lin, Zhongxiang Dai, Daniela Rus, Bryan Kian Hsiang Low
NeurIPS 2025 Adaptive Batch-Wise Sample Scheduling for Direct Preference Optimization Zixuan Huang, Yikun Ban, Lean Fu, Xiaojie Li, Zhongxiang Dai, Jianxin Li, Deqing Wang
JMLR 2025 Adjusted Expected Improvement for Cumulative Regret Minimization in Noisy Bayesian Optimization Shouri Hu, Haowei Wang, Zhongxiang Dai, Bryan Kian Hsiang Low, Szu Hui Ng
NeurIPS 2025 Convergence Rates of Constrained Expected Improvement Haowei Wang, Jingyi Wang, Zhongxiang Dai, Nai-Yuan Chiang, Szu Hui Ng, Cosmin G. Petra
ICLRW 2025 Large Language Model-Enhanced Multi-Armed Bandits Jiahang Sun, Zhiyong Wang, Runhan Yang, Chenjun Xiao, John C.S. Lui, Zhongxiang Dai
ICLRW 2025 Meta-Prompt Optimization for LLM-Based Sequential Decision Making Mingze Kong, Zhiyong Wang, Yao Shu, Zhongxiang Dai
ICLR 2025 Neural Dueling Bandits: Preference-Based Optimization with Human Feedback Arun Verma, Zhongxiang Dai, Xiaoqiang Lin, Patrick Jaillet, Bryan Kian Hsiang Low
ICML 2025 Online Clustering of Dueling Bandits Zhiyong Wang, Jiahang Sun, Mingze Kong, Jize Xie, Qinghua Hu, John C.S. Lui, Zhongxiang Dai
ICML 2025 Refining Adaptive Zeroth-Order Optimization at Ease Yao Shu, Qixin Zhang, Kun He, Zhongxiang Dai
ICMLW 2024 Heterogeneous Federated Zeroth-Order Optimization Using Gradient Surrogates Yao Shu, Xiaoqiang Lin, Zhongxiang Dai, Bryan Kian Hsiang Low
NeurIPS 2024 Localized Zeroth-Order Prompt Optimization Wenyang Hu, Yao Shu, Zongmin Yu, Zhaoxuan Wu, Xiaoqiang Lin, Zhongxiang Dai, See-Kiong Ng, Bryan Kian Hsiang Low
ICMLW 2024 Localized Zeroth-Order Prompt Optimization Wenyang Hu, Yao Shu, Zongmin Yu, Zhaoxuan Wu, Xiaoqiang Lin, Zhongxiang Dai, See-Kiong Ng, Bryan Kian Hsiang Low
ICMLW 2024 Neural Dueling Bandits Arun Verma, Zhongxiang Dai, Xiaoqiang Lin, Patrick Jaillet, Bryan Kian Hsiang Low
NeurIPS 2024 Prompt Optimization with EASE? Efficient Ordering-Aware Automated Selection of Exemplars Zhaoxuan Wu, Xiaoqiang Lin, Zhongxiang Dai, Wenyang Hu, Yao Shu, See-Kiong Ng, Patrick Jaillet, Bryan Kian Hsiang Low
ICMLW 2024 Prompt Optimization with EASE? Efficient Ordering-Aware Automated Selection of Exemplars Zhaoxuan Wu, Xiaoqiang Lin, Zhongxiang Dai, Wenyang Hu, Yao Shu, See-Kiong Ng, Patrick Jaillet, Bryan Kian Hsiang Low
ICMLW 2024 Prompt Optimization with Human Feedback Xiaoqiang Lin, Zhongxiang Dai, Arun Verma, See-Kiong Ng, Patrick Jaillet, Bryan Kian Hsiang Low
ICLR 2024 Robustifying and Boosting Training-Free Neural Architecture Search Zhenfeng He, Yao Shu, Zhongxiang Dai, Bryan Kian Hsiang Low
ICML 2024 Use Your INSTINCT: INSTruction Optimization for LLMs 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
NeurIPS 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
NeurIPS 2023 Exploiting Correlated Auxiliary Feedback in Parameterized Bandits Arun Verma, Zhongxiang Dai, Yao Shu, Bryan Kian Hsiang Low
ICLR 2023 Federated Neural Bandits Zhongxiang Dai, Yao Shu, Arun Verma, Flint Xiaofeng Fan, Bryan Kian Hsiang Low, Patrick Jaillet
NeurIPS 2023 Quantum Bayesian Optimization Zhongxiang Dai, Gregory Kang Ruey Lau, Arun Verma, Yao Shu, Bryan Kian Hsiang Low, Patrick Jaillet
ICML 2023 Training-Free Neural Active Learning with Initialization-Robustness Guarantees Apivich Hemachandra, Zhongxiang Dai, Jasraj Singh, See-Kiong Ng, Bryan Kian Hsiang Low
NeurIPSW 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
ICLR 2023 Zeroth-Order Optimization with Trajectory-Informed Derivative Estimation Yao Shu, Zhongxiang Dai, Weicong Sng, Arun Verma, Patrick Jaillet, Bryan Kian Hsiang Low
ICML 2022 Bayesian Optimization Under Stochastic Delayed Feedback Arun Verma, Zhongxiang Dai, Bryan Kian Hsiang Low
ICLR 2022 NASI: Label- and Data-Agnostic Neural Architecture Search at Initialization Yao Shu, Shaofeng Cai, Zhongxiang Dai, Beng Chin Ooi, Bryan Kian Hsiang Low
UAI 2022 Neural Ensemble Search via Bayesian Sampling Yao Shu, Yizhou Chen, Zhongxiang Dai, Bryan Kian Hsiang Low
UAI 2022 On Provably Robust Meta-Bayesian Optimization Zhongxiang Dai, Yizhou Chen, Haibin Yu, Bryan Kian Hsiang Low, Patrick Jaillet
NeurIPS 2022 Sample-Then-Optimize Batch Neural Thompson Sampling Zhongxiang Dai, Yao Shu, Bryan Kian Hsiang Low, Patrick Jaillet
NeurIPS 2022 Unifying and Boosting Gradient-Based Training-Free Neural Architecture Search Yao Shu, Zhongxiang Dai, Zhaoxuan Wu, Bryan Kian Hsiang Low
NeurIPS 2021 Differentially Private Federated Bayesian Optimization with Distributed Exploration Zhongxiang Dai, Bryan Kian Hsiang Low, Patrick Jaillet
NeurIPS 2021 Fault-Tolerant Federated Reinforcement Learning with Theoretical Guarantee Xiaofeng Fan, Yining Ma, Zhongxiang Dai, Wei Jing, Cheston Tan, Bryan Kian Hsiang Low
NeurIPS 2021 Optimizing Conditional Value-at-Risk of Black-Box Functions Quoc Phong Nguyen, Zhongxiang Dai, Bryan Kian Hsiang Low, Patrick Jaillet
ICML 2021 Value-at-Risk Optimization with Gaussian Processes Quoc Phong Nguyen, Zhongxiang Dai, Bryan Kian Hsiang Low, Patrick Jaillet
NeurIPS 2020 Federated Bayesian Optimization via Thompson Sampling Zhongxiang Dai, Bryan Kian Hsiang Low, Patrick Jaillet
ICML 2020 Private Outsourced Bayesian Optimization Dmitrii Kharkovskii, Zhongxiang Dai, Bryan Kian Hsiang Low
ICML 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
ICML 2019 Bayesian Optimization Meets Bayesian Optimal Stopping Zhongxiang Dai, Haibin Yu, Bryan Kian Hsiang Low, Patrick Jaillet
UAI 2019 Bayesian Optimization with Binary Auxiliary Information Yehong Zhang, Zhongxiang Dai, Bryan Kian Hsiang Low
NeurIPS 2019 Implicit Posterior Variational Inference for Deep Gaussian Processes Haibin Yu, Yizhou Chen, Bryan Kian Hsiang Low, Patrick Jaillet, Zhongxiang Dai