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Patrick Jaillet

49 papers · 2013–2025 · 8 conferences · across top CS/AI conferences

Achievements

πŸƒ Academic Marathon (12) 🐝 Cross-Pollinator (10) 🌈 Renaissance Researcher (6) πŸ—ΊοΈ Taxonomy Completionist (15) 🧭 Keyword Pioneer 🐣 Hot Topic Early Bird πŸŒ‰ Interdisciplinary Bridge 🌍 Conference Polyglot (8) πŸ”¬ Deep Specialist (14) πŸ† Keyword Champion (2) 🀝 Dynamic Duo (33) πŸ† Grand Slam πŸ‘‘ Triple Crown πŸ—ƒοΈ Keyword Collector (156) ❓ The Questioner ⚑ Prolific Year (12) πŸ“ˆ Trend Setter πŸ’Ž Century Club (49) πŸ”₯ Unstoppable (7)

Conferences

NIPS (19) ICML (13) ICLR (6) AISTATS (3) UAI (3) AAAI (2) COLT (2) IJCAI (1)

Top co-authors

Bryan Kian Hsiang Low (33) Zhongxiang Dai (16) Quoc Phong Nguyen (13) YAO SHU (6) Arun Verma (5) Jason Cheuk Nam Liang (4) Negin Golrezaei (4) Ashkan Soleymani (4) Moise Blanchard (3) Stefanie Jegelka (3)

Keywords

bayesian optimization (15) gaussian process (10) regret bound (9) thompson sampling (6) multi-armed bandit (4) upper confidence bound (4) acquisition function (3) black-box optimization (3) no-regret learning (2) online learning (2) batch optimization (2) differential privacy (2) memory complexity (2) nash equilibrium (2) game theory (2) active learning (2) convex optimization (2) federated learning (2) model fusion (2) robust optimization (2)

Papers

A Robust Kernel Statistical Test of Invariance: Detecting Subtle Asymmetries AISTATS 2025
Neural Dueling Bandits: Preference-Based Optimization with Human Feedback ICLR 2025
Non-Monetary Mechanism Design without Distributional Information: Using Scarce Audits Wisely (Extended Abstract) COLT 2025
Learning with Exact Invariances in Polynomial Time ICML 2025
A Universal Class of Sharpness-Aware Minimization Algorithms ICML 2024
Use Your INSTINCT: INSTruction optimization for LLMs usIng Neural bandits Coupled with Transformers ICML 2024
Optimistic Bayesian Optimization with Unknown Constraints ICLR 2024
Meta-VBO: Utilizing Prior Tasks in Optimizing Risk Measures with Gaussian Processes ICLR 2024
Deletion-Anticipative Data Selection with a Limited Budget ICML 2024
Active Set Ordering NIPS 2024
Prompt Optimization with EASE? Efficient Ordering-aware Automated Selection of Exemplars NIPS 2024
Quadratic Memory is Necessary for Optimal Query Complexity in Convex Optimization: Center-of-Mass is Pareto-Optimal COLT 2023
Federated Neural Bandits ICLR 2023
Memory-Constrained Algorithms for Convex Optimization NIPS 2023
Incentives in Private Collaborative Machine Learning NIPS 2023
Quantum Bayesian Optimization NIPS 2023
Batch Bayesian Optimization For Replicable Experimental Design NIPS 2023
Pricing against a Budget and ROI Constrained Buyer AISTATS 2023
Multi-channel Autobidding with Budget and ROI Constraints ICML 2023
DRCFS: Doubly Robust Causal Feature Selection ICML 2023
Incentive-aware Contextual Pricing with Non-parametric Market Noise AISTATS 2023
Risk-Aware Reinforcement Learning with Coherent Risk Measures and Non-linear Function Approximation ICLR 2023
Zeroth-Order Optimization with Trajectory-Informed Derivative Estimation ICLR 2023
On provably robust meta-Bayesian optimization UAI 2022
Effective Dimension in Bandit Problems under Censorship NIPS 2022
Sample-Then-Optimize Batch Neural Thompson Sampling NIPS 2022
Trade-off between Payoff and Model Rewards in Shapley-Fair Collaborative Machine Learning NIPS 2022
Top-k Ranking Bayesian Optimization AAAI 2021
An Information-Theoretic Framework for Unifying Active Learning Problems AAAI 2021
Differentially Private Federated Bayesian Optimization with Distributed Exploration NIPS 2021
Optimizing Conditional Value-At-Risk of Black-Box Functions NIPS 2021
Model Fusion for Personalized Learning ICML 2021
Value-at-Risk Optimization with Gaussian Processes ICML 2021
Collaborative Bayesian Optimization with Fair Regret ICML 2021
Learning to learn with Gaussian processes UAI 2021
Trusted-maximizers entropy search for efficient Bayesian optimization UAI 2021
No-regret Learning in Price Competitions under Consumer Reference Effects NIPS 2020
Variational Bayesian Unlearning NIPS 2020
Federated Bayesian Optimization via Thompson Sampling NIPS 2020
R2-B2: Recursive Reasoning-Based Bayesian Optimization for No-Regret Learning in Games ICML 2020
Learning Task-Agnostic Embedding of Multiple Black-Box Experts for Multi-Task Model Fusion ICML 2020
Bayesian Optimization Meets Bayesian Optimal Stopping ICML 2019
Improving Customer Satisfaction in Bike Sharing Systems through Dynamic Repositioning IJCAI 2019
Implicit Posterior Variational Inference for Deep Gaussian Processes NIPS 2019
Online Learning with a Hint NIPS 2017
Real-Time Bidding with Side Information NIPS 2017
Inverse Reinforcement Learning with Locally Consistent Reward Functions NIPS 2015
Nonmyopic Ξ΅-Bayes-Optimal Active Learning of Gaussian Processes ICML 2014
Regret based Robust Solutions for Uncertain Markov Decision Processes NIPS 2013