Jaillet, Patrick

68 publications

AISTATS 2025 A Robust Kernel Statistical Test of Invariance: Detecting Subtle Asymmetries Ashkan Soleymani, Behrooz Tahmasebi, Stefanie Jegelka, Patrick Jaillet

TMLR 2025 Double Machine Learning Based Structure Identification from Temporal Data Emmanouil Angelis, Francesco Quinzan, Ashkan Soleymani, Patrick Jaillet, Stefan Bauer

NeurIPS 2025 Incentive-Aware Dynamic Resource Allocation Under Long-Term Cost Constraints Yan Dai, Negin Golrezaei, Patrick Jaillet

ICML 2025 Learning with Exact Invariances in Polynomial Time Ashkan Soleymani, Behrooz Tahmasebi, Stefanie Jegelka, Patrick Jaillet

ICLR 2025 Neural Dueling Bandits: Preference-Based Optimization with Human Feedback Arun Verma, Zhongxiang Dai, Xiaoqiang Lin, Patrick Jaillet, Bryan Kian Hsiang Low

COLT 2025 Non-Monetary Mechanism Design Without Distributional Information: Using Scarce Audits Wisely (Extended Abstract) Yan Dai, Moïse Blanchard, Patrick Jaillet

ICML 2024 A Universal Class of Sharpness-Aware Minimization Algorithms Behrooz Tahmasebi, Ashkan Soleymani, Dara Bahri, Stefanie Jegelka, Patrick Jaillet

ICMLW 2024 A Universal Class of Sharpness-Aware Minimization Algorithms Behrooz Tahmasebi, Ashkan Soleymani, Dara Bahri, Stefanie Jegelka, Patrick Jaillet

NeurIPS 2024 Active Set Ordering Quoc Phong Nguyen, Sunil Gupta, Svetha Venkatesh, Bryan Kian Hsiang Low, Patrick Jaillet

ICML 2024 Deletion-Anticipative Data Selection with a Limited Budget Rachael Hwee Ling Sim, Jue Fan, Xiao Tian, Patrick Jaillet, Bryan Kian Hsiang Low

ICLR 2024 Meta-VBO: Utilizing Prior Tasks in Optimizing Risk Measures with Gaussian Processes Quoc Phong Nguyen, Bryan Kian Hsiang Low, Patrick Jaillet

ICMLW 2024 Neural Dueling Bandits Arun Verma, Zhongxiang Dai, Xiaoqiang Lin, Patrick Jaillet, Bryan Kian Hsiang Low

ICLR 2024 Optimistic Bayesian Optimization with Unknown Constraints Quoc Phong Nguyen, Wan Theng Ruth Chew, Le Song, Bryan Kian Hsiang Low, Patrick Jaillet

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

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

ICML 2023 DRCFS: Doubly Robust Causal Feature Selection Francesco Quinzan, Ashkan Soleymani, Patrick Jaillet, Cristian R. Rojas, Stefan Bauer

ICLR 2023 Federated Neural Bandits Zhongxiang Dai, Yao Shu, Arun Verma, Flint Xiaofeng Fan, Bryan Kian Hsiang Low, Patrick Jaillet

AISTATS 2023 Incentive-Aware Contextual Pricing with Non-Parametric Market Noise Negin Golrezaei, Patrick Jaillet, Jason Cheuk Nam Liang

NeurIPS 2023 Incentives in Private Collaborative Machine Learning Rachael Sim, Yehong Zhang, Nghia Hoang, Xinyi Xu, Bryan Kian Hsiang Low, Patrick Jaillet

NeurIPS 2023 Memory-Constrained Algorithms for Convex Optimization Moise Blanchard, Junhui Zhang, Patrick Jaillet

ICML 2023 Multi-Channel Autobidding with Budget and ROI Constraints Yuan Deng, Negin Golrezaei, Patrick Jaillet, Jason Cheuk Nam Liang, Vahab Mirrokni

NeurIPSW 2023 On Scale-Invariant Sharpness Measures Behrooz Tahmasebi, Ashkan Soleymani, Stefanie Jegelka, Patrick Jaillet

AISTATS 2023 Pricing Against a Budget and ROI Constrained Buyer Negin Golrezaei, Patrick Jaillet, Jason Cheuk Nam Liang, Vahab Mirrokni

COLT 2023 Quadratic Memory Is Necessary for Optimal Query Complexity in Convex Optimization: Center-of-Mass Is Pareto-Optimal Moïse Blanchard, Junhui Zhang, Patrick Jaillet

NeurIPS 2023 Quantum Bayesian Optimization Zhongxiang Dai, Gregory Kang Ruey Lau, Arun Verma, Yao Shu, Bryan Kian Hsiang Low, Patrick Jaillet

ICLR 2023 Risk-Aware Reinforcement Learning with Coherent Risk Measures and Non-Linear Function Approximation Thanh Lam, Arun Verma, Bryan Kian Hsiang Low, Patrick Jaillet

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

NeurIPS 2022 Effective Dimension in Bandit Problems Under Censorship Gauthier Guinet, Saurabh Amin, Patrick Jaillet

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 Trade-Off Between Payoff and Model Rewards in Shapley-Fair Collaborative Machine Learning Quoc Phong Nguyen, Bryan Kian Hsiang Low, Patrick Jaillet

AAAI 2021 An Information-Theoretic Framework for Unifying Active Learning Problems Quoc Phong Nguyen, Bryan Kian Hsiang Low, Patrick Jaillet

ICML 2021 Collaborative Bayesian Optimization with Fair Regret Rachael Hwee Ling Sim, Yehong Zhang, Bryan Kian Hsiang Low, Patrick Jaillet

NeurIPS 2021 Differentially Private Federated Bayesian Optimization with Distributed Exploration Zhongxiang Dai, Bryan Kian Hsiang Low, Patrick Jaillet

UAI 2021 Learning to Learn with Gaussian Processes Quoc Phong Nguyen, Bryan Kian Hsiang Low, Patrick Jaillet

ICML 2021 Model Fusion for Personalized Learning Thanh Chi Lam, Nghia Hoang, Bryan Kian Hsiang Low, Patrick Jaillet

NeurIPS 2021 Optimizing Conditional Value-at-Risk of Black-Box Functions Quoc Phong Nguyen, Zhongxiang Dai, Bryan Kian Hsiang Low, Patrick Jaillet

AAAI 2021 Top-K Ranking Bayesian Optimization Quoc Phong Nguyen, Sebastian Tay, Bryan Kian Hsiang Low, Patrick Jaillet

UAI 2021 Trusted-Maximizers Entropy Search for Efficient Bayesian Optimization Quoc Phong Nguyen, Zhaoxuan Wu, 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

JAIR 2021 Zone pAth Construction (ZAC) Based Approaches for Effective Real-Time Ridesharing Meghna Lowalekar, Pradeep Varakantham, Patrick Jaillet

NeurIPS 2020 Federated Bayesian Optimization via Thompson Sampling Zhongxiang Dai, Bryan Kian Hsiang Low, Patrick Jaillet

ICML 2020 Learning Task-Agnostic Embedding of Multiple Black-Box Experts for Multi-Task Model Fusion Nghia Hoang, Thanh Lam, Bryan Kian Hsiang Low, Patrick Jaillet

NeurIPS 2020 No-Regret Learning in Price Competitions Under Consumer Reference Effects Negin Golrezaei, Patrick Jaillet, Jason Cheuk Nam Liang

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

NeurIPS 2020 Variational Bayesian Unlearning Quoc Phong Nguyen, Bryan Kian Hsiang Low, Patrick Jaillet

ICML 2019 Bayesian Optimization Meets Bayesian Optimal Stopping Zhongxiang Dai, Haibin Yu, Bryan Kian Hsiang Low, Patrick Jaillet

NeurIPS 2019 Implicit Posterior Variational Inference for Deep Gaussian Processes Haibin Yu, Yizhou Chen, Bryan Kian Hsiang Low, Patrick Jaillet, Zhongxiang Dai

IJCAI 2019 Improving Customer Satisfaction in Bike Sharing Systems Through Dynamic Repositioning Supriyo Ghosh, Jing Yu Koh, Patrick Jaillet

JAIR 2017 Dynamic Repositioning to Reduce Lost Demand in Bike Sharing Systems Supriyo Ghosh, Pradeep Varakantham, Yossiri Adulyasak, Patrick Jaillet

NeurIPS 2017 Online Learning with a Hint Ofer Dekel, Arthur Flajolet, Nika Haghtalab, Patrick Jaillet

NeurIPS 2017 Real-Time Bidding with Side Information Arthur Flajolet, Patrick Jaillet

JAIR 2017 Sampling Based Approaches for Minimizing Regret in Uncertain Markov Decision Processes (MDPs) Asrar Ahmed, Pradeep Varakantham, Meghna Lowalekar, Yossiri Adulyasak, Patrick Jaillet

AAAI 2016 Gaussian Process Planning with Lipschitz Continuous Reward Functions: Towards Unifying Bayesian Optimization, Active Learning, and Beyond Chun Kai Ling, Kian Hsiang Low, Patrick Jaillet

AAAI 2016 Online Spatio-Temporal Matching in Stochastic and Dynamic Domains Meghna Lowalekar, Pradeep Varakantham, Patrick Jaillet

NeurIPS 2015 Inverse Reinforcement Learning with Locally Consistent Reward Functions Quoc Phong Nguyen, Bryan Kian Hsiang Low, Patrick Jaillet

AAAI 2015 Parallel Gaussian Process Regression for Big Data: Low-Rank Representation Meets Markov Approximation Kian Hsiang Low, Jiangbo Yu, Jie Chen, Patrick Jaillet

AAAI 2015 Solving Uncertain MDPs with Objectives That Are Separable over Instantiations of Model Uncertainty Yossiri Adulyasak, Pradeep Varakantham, Asrar Ahmed, Patrick Jaillet

ECML-PKDD 2014 Active Learning Is Planning: Nonmyopic Ε-Bayes-Optimal Active Learning of Gaussian Processes Trong Nghia Hoang, Kian Hsiang Low, Patrick Jaillet, Mohan S. Kankanhalli

AAAI 2014 Decentralized Stochastic Planning with Anonymity in Interactions Pradeep Varakantham, Yossiri Adulyasak, Patrick Jaillet

ICML 2014 Nonmyopic Ε-Bayes-Optimal Active Learning of Gaussian Processes Trong Nghia Hoang, Bryan Kian Hsiang Low, Patrick Jaillet, Mohan Kankanhalli

UAI 2013 Parallel Gaussian Process Regression with Low-Rank Covariance Matrix Approximations Jie Chen, Nannan Cao, Kian Hsiang Low, Ruofei Ouyang, Colin Keng-Yan Tan, Patrick Jaillet

NeurIPS 2013 Regret Based Robust Solutions for Uncertain Markov Decision Processes Asrar Ahmed, Pradeep Varakantham, Yossiri Adulyasak, Patrick Jaillet

UAI 2012 Decentralized Data Fusion and Active Sensing with Mobile Sensors for Modeling and Predicting Spatiotemporal Traffic Phenomena Jie Chen, Kian Hsiang Low, Colin Keng-Yan Tan, Ali Oran, Patrick Jaillet, John M. Dolan, Gaurav S. Sukhatme