Patrick Jaillet

ORCID

Publication Activity (10 Years)

Years Active: 1988-2024
Publications (10 Years): 159

Top Venues

Publications

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 (2024)
Xiaoqiang Lin, Zhongxiang Dai, Arun Verma, See-Kiong Ng, Patrick Jaillet, Bryan Kian Hsiang Low
Prompt Optimization with Human Feedback. CoRR (2024)
Quoc Phong Nguyen, Wan Theng Ruth Chew, Le Song, Bryan Kian Hsiang Low, Patrick Jaillet
Optimistic Bayesian Optimization with Unknown Constraints. ICLR (2024)
Patrick Jaillet, Chara Podimata, Zijie Zhou
Grace Period is All You Need: Individual Fairness without Revenue Loss in Revenue Management. CoRR (2024)
Quoc Phong Nguyen, Bryan Kian Hsiang Low, Patrick Jaillet
Meta-VBO: Utilizing Prior Tasks in Optimizing Risk Measures with Gaussian Processes. ICLR (2024)
Arun Verma, Zhongxiang Dai, Xiaoqiang Lin, Patrick Jaillet, Bryan Kian Hsiang Low
Neural Dueling Bandits. CoRR (2024)
Moïse Blanchard, Alexandre Jacquillat, Patrick Jaillet
-Traveling Salesman Problem and the Traveling Repairman Problem. Math. Oper. Res. 49 (2) (2024)
Rachael Hwee Ling Sim, Yehong Zhang, Trong Nghia Hoang, Xinyi Xu, Bryan Kian Hsiang Low, Patrick Jaillet
Incentives in Private Collaborative Machine Learning. CoRR (2024)
Yuan Deng, Negin Golrezaei, Patrick Jaillet, Jason Cheuk Nam Liang, Vahab Mirrokni
Individual Welfare Guarantees in the Autobidding World with Machine-learned Advice. WWW (2024)
Behrooz Tahmasebi, Ashkan Soleymani, Dara Bahri, Stefanie Jegelka, Patrick Jaillet
A Universal Class of Sharpness-Aware Minimization Algorithms. CoRR (2024)
Francesco Quinzan, Ashkan Soleymani, Patrick Jaillet, Cristian R. Rojas, Stefan Bauer
DRCFS: Doubly Robust Causal Feature Selection. ICML (2023)
Rachael Hwee Ling Sim, Yehong Zhang, Nghia Hoang, Xinyi Xu, Bryan Kian Hsiang Low, Patrick Jaillet
Incentives in Private Collaborative Machine Learning. NeurIPS (2023)
Yuan Deng, Negin Golrezaei, Patrick Jaillet, Jason Cheuk Nam Liang, Vahab Mirrokni
Multi-channel Autobidding with Budget and ROI Constraints. ICML (2023)
Sohil Shah, Saurabh Amin, Patrick Jaillet
Information Disclosure About Booster Efficacy in a Non-Stationary Environment. CDC (2023)
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)
Yao Shu, Zhongxiang Dai, Weicong Sng, Arun Verma, Patrick Jaillet, Bryan Kian Hsiang Low
Zeroth-Order Optimization with Trajectory-Informed Derivative Estimation. ICLR (2023)
Saurabh Amin, Patrick Jaillet, Haripriya Pulyassary, Manxi Wu
Market Design for Dynamic Pricing and Pooling in Capacitated Networks. CoRR (2023)
Negin Golrezaei, Patrick Jaillet, Zijie Zhou
Online Resource Allocation with Convex-set Machine-Learned Advice. CoRR (2023)
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 (2023)
Negin Golrezaei, Patrick Jaillet, Jason Cheuk Nam Liang
Incentive-aware Contextual Pricing with Non-parametric Market Noise. AISTATS (2023)
Sohil Shah, Saurabh Amin, Patrick Jaillet
Information Design for Hybrid Work under Infectious Disease Transmission Risk. CoRR (2023)
Moïse Blanchard, Steve Hanneke, Patrick Jaillet
Contextual Bandits and Optimistically Universal Learning. CoRR (2023)
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 (2023)
Rafael Hanashiro, Patrick Jaillet
Distribution-Dependent Rates for Multi-Distribution Learning. CoRR (2023)
Yuan Deng, Negin Golrezaei, Patrick Jaillet, Jason Cheuk Nam Liang, Vahab Mirrokni
Multi-channel Autobidding with Budget and ROI Constraints. CoRR (2023)
Moïse Blanchard, Junhui Zhang, Patrick Jaillet
Quadratic Memory is Necessary for Optimal Query Complexity in Convex Optimization: Center-of-Mass is Pareto-Optimal. CoRR (2023)
Itai Ashlagi, Maximilien Burq, Chinmoy Dutta, Patrick Jaillet, Amin Saberi, Chris Sholley
Edge-Weighted Online Windowed Matching. Math. Oper. Res. 48 (2) (2023)
Moïse Blanchard, Junhui Zhang, Patrick Jaillet
Memory-Constrained Algorithms for Convex Optimization. NeurIPS (2023)
Negin Golrezaei, Patrick Jaillet, Jason Cheuk Nam Liang, Vahab Mirrokni
Pricing against a Budget and ROI Constrained Buyer. AISTATS (2023)
Zhongxiang Dai, Gregory Kang Ruey Lau, Arun Verma, Yao Shu, Bryan Kian Hsiang Low, Patrick Jaillet
Quantum Bayesian Optimization. CoRR (2023)
Moïse Blanchard, Junhui Zhang, Patrick Jaillet
Quadratic Memory is Necessary for Optimal Query Complexity in Convex Optimization: Center-of-Mass is Pareto-Optimal. COLT (2023)
Zhongxiang Dai, Gregory Kang Ruey Lau, Arun Verma, Yao Shu, Bryan Kian Hsiang Low, Patrick Jaillet
Quantum Bayesian Optimization. NeurIPS (2023)
Emmanouil Angelis, Francesco Quinzan, Ashkan Soleymani, Patrick Jaillet, Stefan Bauer
Doubly Robust Structure Identification from Temporal Data. CoRR (2023)
Moïse Blanchard, Steve Hanneke, Patrick Jaillet
Non-stationary Contextual Bandits and Universal Learning. CoRR (2023)
Gauthier Guinet, Saurabh Amin, Patrick Jaillet
Effective Dimension in Bandit Problems under Censorship. CoRR (2023)
Zhongxiang Dai, Yao Shu, Arun Verma, Flint Xiaofeng Fan, Bryan Kian Hsiang Low, Patrick Jaillet
Federated Neural Bandits. ICLR (2023)
Moïse Blanchard, Junhui Zhang, Patrick Jaillet
Memory-Constrained Algorithms for Convex Optimization via Recursive Cutting-Planes. CoRR (2023)
Francesco Quinzan, Ashkan Soleymani, Patrick Jaillet, Cristian R. Rojas, Stefan Bauer
DRCFS: Doubly Robust Causal Feature Selection. CoRR (2023)
Junhui Zhang, Patrick Jaillet
Secretary Problems with Random Number of Candidates: How Prior Distributional Information Helps. CoRR (2023)
Thanh Lam, Arun Verma, Bryan Kian Hsiang Low, Patrick Jaillet
Risk-Aware Reinforcement Learning with Coherent Risk Measures and Non-linear Function Approximation. ICLR (2023)
Moïse Blanchard, Patrick Jaillet
Universal Regression with Adversarial Responses. CoRR (2022)
Quoc Phong Nguyen, Bryan Kian Hsiang Low, Patrick Jaillet
Trade-off between Payoff and Model Rewards in Shapley-Fair Collaborative Machine Learning. NeurIPS (2022)
Quoc Phong Nguyen, Bryan Kian Hsiang Low, Patrick Jaillet
Rectified Max-Value Entropy Search for Bayesian Optimization. CoRR (2022)
Moïse Blanchard, Alexandre Jacquillat, Patrick Jaillet
Probabilistic bounds on the k-Traveling Salesman Problem and the Traveling Repairman Problem. CoRR (2022)
Patrick Jaillet, Gar Goei Loke, Melvyn Sim
Strategic Workforce Planning Under Uncertainty. Oper. Res. 70 (2) (2022)
Sohil Shah, Saurabh Amin, Patrick Jaillet
Optimal Information Provision for Strategic Hybrid Workers. CDC (2022)
Sohil Shah, Saurabh Amin, Patrick Jaillet
Optimal Information Provision for Strategic Hybrid Workers. CoRR (2022)
Zhongxiang Dai, Yao Shu, Arun Verma, Flint Xiaofeng Fan, Bryan Kian Hsiang Low, Patrick Jaillet
Federated Neural Bandit. CoRR (2022)
Zhongxiang Dai, Yizhou Chen, Haibin Yu, Bryan Kian Hsiang Low, Patrick Jaillet
On Provably Robust Meta-Bayesian Optimization. CoRR (2022)
Zhongxiang Dai, Yizhou Chen, Haibin Yu, Bryan Kian Hsiang Low, Patrick Jaillet
On provably robust meta-Bayesian optimization. UAI (2022)
Zhongxiang Dai, Yao Shu, Bryan Kian Hsiang Low, Patrick Jaillet
Sample-Then-Optimize Batch Neural Thompson Sampling. CoRR (2022)
Yuan Deng, Negin Golrezaei, Patrick Jaillet, Jason Cheuk Nam Liang, Vahab Mirrokni
Fairness in the Autobidding World with Machine-learned Advice. CoRR (2022)
Zhongxiang Dai, Yao Shu, Bryan Kian Hsiang Low, Patrick Jaillet
Sample-Then-Optimize Batch Neural Thompson Sampling. NeurIPS (2022)
Moïse Blanchard, Alexandre Jacquillat, Patrick Jaillet
Additional Results and Extensions for the paper "Probabilistic bounds on the k-Traveling Salesman Problem and the Traveling Repairman Problem". CoRR (2022)
Gauthier Guinet, Saurabh Amin, Patrick Jaillet
Effective Dimension in Bandit Problems under Censorship. NeurIPS (2022)
The Viet Bui, Tien Mai, Patrick Jaillet
Weighted Maximum Entropy Inverse Reinforcement Learning. CoRR (2022)
Supriyo Ghosh, Patrick Jaillet
An iterative security game for computing robust and adaptive network flows. Comput. Oper. Res. 138 (2022)
Mathieu Dahan, Saurabh Amin, Patrick Jaillet
Probability Distributions on Partially Ordered Sets and Network Interdiction Games. Math. Oper. Res. 47 (1) (2022)
Patrick Jaillet, Sanjay Dominik Jena, Tsan Sheng Adam Ng, Melvyn Sim
Satisficing Models Under Uncertainty. INFORMS J. Optim. 4 (4) (2022)
Seyed Hossein Hashemi Doulabi, Patrick Jaillet, Gilles Pesant, Louis-Martin Rousseau
Exploiting the Structure of Two-Stage Robust Optimization Models with Exponential Scenarios. INFORMS J. Comput. 33 (1) (2021)
Saurabh Amin, Patrick Jaillet, Manxi Wu
Efficient Carpooling and Toll Pricing for Autonomous Transportation. CoRR (2021)
Quoc Phong Nguyen, Bryan Kian Hsiang Low, Patrick Jaillet
Learning to learn with Gaussian processes. UAI (2021)
Negin Golrezaei, Patrick Jaillet, Jason Cheuk Nam Liang, Vahab S. Mirrokni
Bidding and Pricing in Budget and ROI Constrained Markets. CoRR (2021)
Rachael Hwee Ling Sim, Yehong Zhang, Bryan Kian Hsiang Low, Patrick Jaillet
Collaborative Bayesian Optimization with Fair Regret. ICML (2021)
Quoc Phong Nguyen, Zhongxiang Dai, Bryan Kian Hsiang Low, Patrick Jaillet
Value-at-Risk Optimization with Gaussian Processes. ICML (2021)
Quoc Phong Nguyen, Sebastian Tay, Bryan Kian Hsiang Low, Patrick Jaillet
Top-k Ranking Bayesian Optimization. AAAI (2021)
Quoc Phong Nguyen, Bryan Kian Hsiang Low, Patrick Jaillet
An Information-Theoretic Framework for Unifying Active Learning Problems. AAAI (2021)
Thanh Chi Lam, Trong Nghia Hoang, Bryan Kian Hsiang Low, Patrick Jaillet
Model Fusion for Personalized Learning. ICML (2021)
Florian Delavernhe, Patrick Jaillet, André Rossi, Marc Sevaux
Planning a multi-sensors search for a moving target considering traveling costs. Eur. J. Oper. Res. 292 (2) (2021)
Quoc Phong Nguyen, Zhaoxuan Wu, Bryan Kian Hsiang Low, Patrick Jaillet
Trusted-maximizers entropy search for efficient Bayesian optimization. UAI (2021)
Maaike Hoogeboom, Yossiri Adulyasak, Wout Dullaert, Patrick Jaillet
The Robust Vehicle Routing Problem with Time Window Assignments. Transp. Sci. 55 (2) (2021)
Zhongxiang Dai, Bryan Kian Hsiang Low, Patrick Jaillet
Differentially Private Federated Bayesian Optimization with Distributed Exploration. NeurIPS (2021)
Haibin Yu, Dapeng Liu, Bryan Kian Hsiang Low, Patrick Jaillet
Convolutional Normalizing Flows for Deep Gaussian Processes. IJCNN (2021)
Tien Mai, Patrick Jaillet
Robust Entropy-regularized Markov Decision Processes. CoRR (2021)
Quoc Phong Nguyen, Zhaoxuan Wu, Bryan Kian Hsiang Low, Patrick Jaillet
Trusted-Maximizers Entropy Search for Efficient Bayesian Optimization. CoRR (2021)
Haibin Yu, Dapeng Liu, Bryan Kian Hsiang Low, Patrick Jaillet
Convolutional Normalizing Flows for Deep Gaussian Processes. CoRR (2021)
Quoc Phong Nguyen, Zhongxiang Dai, Bryan Kian Hsiang Low, Patrick Jaillet
Value-at-Risk Optimization with Gaussian Processes. CoRR (2021)
Quoc Phong Nguyen, Zhongxiang Dai, Bryan Kian Hsiang Low, Patrick Jaillet
Optimizing Conditional Value-At-Risk of Black-Box Functions. NeurIPS (2021)
Meghna Lowalekar, Pradeep Varakantham, Patrick Jaillet
Zone pAth Construction (ZAC) based Approaches for Effective Real-Time Ridesharing. J. Artif. Intell. Res. 70 (2021)
Dawsen Hwang, Patrick Jaillet, Vahideh H. Manshadi
Online Resource Allocation Under Partially Predictable Demand. Oper. Res. 69 (3) (2021)
Zhongxiang Dai, Bryan Kian Hsiang Low, Patrick Jaillet
Differentially Private Federated Bayesian Optimization with Distributed Exploration. CoRR (2021)
Youssef M. Aboutaleb, Moshe E. Ben-Akiva, Patrick Jaillet
Learning Structure in Nested Logit Models. CoRR (2020)
Quoc Phong Nguyen, Bryan Kian Hsiang Low, Patrick Jaillet
An Information-Theoretic Framework for Unifying Active Learning Problems. CoRR (2020)
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 (2020)
Quoc Phong Nguyen, Bryan Kian Hsiang Low, Patrick Jaillet
Variational Bayesian Unlearning. NeurIPS (2020)
Trong Nghia Hoang, Thanh Lam, Bryan Kian Hsiang Low, Patrick Jaillet
Learning Task-Agnostic Embedding of Multiple Black-Box Experts for Multi-Task Model Fusion. ICML (2020)
Zhongxiang Dai, Kian Hsiang Low, Patrick Jaillet
Federated Bayesian Optimization via Thompson Sampling. CoRR (2020)
Zhongxiang Dai, Bryan Kian Hsiang Low, Patrick Jaillet
Federated Bayesian Optimization via Thompson Sampling. NeurIPS (2020)
Negin Golrezaei, Patrick Jaillet, Jason Cheuk Nam Liang
No-regret Learning in Price Competitions under Consumer Reference Effects. CoRR (2020)
Tien Mai, Patrick Jaillet
A Relation Analysis of Markov Decision Process Frameworks. CoRR (2020)
Meghna Lowalekar, Pradeep Varakantham, Patrick Jaillet
Competitive Ratios for Online Multi-capacity Ridesharing. CoRR (2020)
Konstantina Mellou, Luke Marshall, Krishna Chintalapudi, Patrick Jaillet, Ishai Menache
Optimizing Onsite Food Services at Scale. SIGSPATIAL/GIS (2020)
Quoc Phong Nguyen, Sebastian Tay, Bryan Kian Hsiang Low, Patrick Jaillet
Top-k Ranking Bayesian Optimization. CoRR (2020)
Quoc Phong Nguyen, Bryan Kian Hsiang Low, Patrick Jaillet
Variational Bayesian Unlearning. CoRR (2020)
Meghna Lowalekar, Pradeep Varakantham, Patrick Jaillet
Zone pAth Construction (ZAC) based Approaches for Effective Real-Time Ridesharing. CoRR (2020)
Julia Gaudio, Patrick Jaillet
An improved lower bound for the Traveling Salesman constant. Oper. Res. Lett. 48 (1) (2020)
Anatolii Prokhorchuk, Justin Dauwels, Patrick Jaillet
Estimating Travel Time Distributions by Bayesian Network Inference. IEEE Trans. Intell. Transp. Syst. 21 (5) (2020)
Negin Golrezaei, Patrick Jaillet, Jason Cheuk Nam Liang
No-regret Learning in Price Competitions under Consumer Reference Effects. NeurIPS (2020)
Meghna Lowalekar, Pradeep Varakantham, Patrick Jaillet
Competitive Ratios for Online Multi-capacity Ridesharing. AAMAS (2020)
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)

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Publication Activity (10 Years)

Top Topics

Top Venues

Patrick Jaillet