Random Exploration in Bayesian Optimization: Order-Optimal Regret and Computational Efficiency
Fuente:
arXiv
Guardado en:
| Autores principales: | Salgia, Sudeep, Vakili, Sattar, Zhao, Qing |
|---|---|
| Formato: | Preprint |
| Publicado: |
2023
|
| Materias: | |
| Acceso en línea: | |
| Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
Ejemplares similares
Order-Optimal Regret in Distributed Kernel Bandits using Uniform Sampling with Shared Randomness
por: Pavlovic, Nikola, et al.
Publicado: (2024)
por: Pavlovic, Nikola, et al.
Publicado: (2024)
Open Problem: Order Optimal Regret Bounds for Kernel-Based Reinforcement Learning
por: Vakili, Sattar
Publicado: (2024)
por: Vakili, Sattar
Publicado: (2024)
Kernelized Reinforcement Learning with Order Optimal Regret Bounds
por: Vakili, Sattar, et al.
Publicado: (2023)
por: Vakili, Sattar, et al.
Publicado: (2023)
Distributed Linear Bandits under Communication Constraints
por: Salgia, Sudeep, et al.
Publicado: (2022)
por: Salgia, Sudeep, et al.
Publicado: (2022)
Differential Privacy in Kernelized Contextual Bandits via Random Projections
por: Pavlovic, Nikola, et al.
Publicado: (2025)
por: Pavlovic, Nikola, et al.
Publicado: (2025)
Bayesian Optimization from Human Feedback: Near-Optimal Regret Bounds
por: Kayal, Aya, et al.
Publicado: (2025)
por: Kayal, Aya, et al.
Publicado: (2025)
Differentially Private Kernelized Contextual Bandits
por: Pavlovic, Nikola, et al.
Publicado: (2025)
por: Pavlovic, Nikola, et al.
Publicado: (2025)
Characterizing the Accuracy-Communication-Privacy Trade-off in Distributed Stochastic Convex Optimization
por: Salgia, Sudeep, et al.
Publicado: (2025)
por: Salgia, Sudeep, et al.
Publicado: (2025)
Kernel-Based Function Approximation for Average Reward Reinforcement Learning: An Optimist No-Regret Algorithm
por: Vakili, Sattar, et al.
Publicado: (2024)
por: Vakili, Sattar, et al.
Publicado: (2024)
The Sample-Communication Complexity Trade-off in Federated Q-Learning
por: Salgia, Sudeep, et al.
Publicado: (2024)
por: Salgia, Sudeep, et al.
Publicado: (2024)
Learning Kernel-Based MDPs from Episodic Preferential Feedback
por: Pavlovic, Nikola, et al.
Publicado: (2026)
por: Pavlovic, Nikola, et al.
Publicado: (2026)
No-Regret Thompson Sampling for Finite-Horizon Markov Decision Processes with Gaussian Processes
por: Bayrooti, Jasmine, et al.
Publicado: (2025)
por: Bayrooti, Jasmine, et al.
Publicado: (2025)
A Finite Time Analysis of Thompson Sampling for Bayesian Optimization with Preferential Feedback
por: Lazzaro, Joseph, et al.
Publicado: (2026)
por: Lazzaro, Joseph, et al.
Publicado: (2026)
Near-Optimal Sample Complexity in Reward-Free Kernel-Based Reinforcement Learning
por: Kayal, Aya, et al.
Publicado: (2025)
por: Kayal, Aya, et al.
Publicado: (2025)
Randomized Kriging Believer for Parallel Bayesian Optimization with Regret Bounds
por: Sugiura, Shuhei, et al.
Publicado: (2026)
por: Sugiura, Shuhei, et al.
Publicado: (2026)
Optimal-Point Variance Reduction For Bayesian Optimization With Regret Guarantee
por: Takeno, Shion
Publicado: (2026)
por: Takeno, Shion
Publicado: (2026)
Direct Regret Optimization in Bayesian Optimization
por: Zhang, Fengxue, et al.
Publicado: (2025)
por: Zhang, Fengxue, et al.
Publicado: (2025)
Order Optimal Regret Bounds for Sharpe Ratio Optimization under Thompson Sampling
por: Shah, Mohammad Taha, et al.
Publicado: (2025)
por: Shah, Mohammad Taha, et al.
Publicado: (2025)
Optimal Bayesian Affine Estimator and Active Learning for the Wiener Model
por: Vakili, Sasan, et al.
Publicado: (2025)
por: Vakili, Sasan, et al.
Publicado: (2025)
Stopping Bayesian Optimization with Probabilistic Regret Bounds
por: Wilson, James T.
Publicado: (2024)
por: Wilson, James T.
Publicado: (2024)
Beyond Regrets: Geometric Metrics for Bayesian Optimization
por: Kim, Jungtaek
Publicado: (2024)
por: Kim, Jungtaek
Publicado: (2024)
On Regret Bounds of Thompson Sampling for Bayesian Optimization
por: Takeno, Shion, et al.
Publicado: (2026)
por: Takeno, Shion, et al.
Publicado: (2026)
Reinforcement Learning Using known Invariances
por: Cioba, Alexandru, et al.
Publicado: (2025)
por: Cioba, Alexandru, et al.
Publicado: (2025)
Optimal Regret for Policy Optimization in Contextual Bandits
por: Levy, Orin, et al.
Publicado: (2026)
por: Levy, Orin, et al.
Publicado: (2026)
Posterior Sampling-Based Bayesian Optimization with Tighter Bayesian Regret Bounds
por: Takeno, Shion, et al.
Publicado: (2023)
por: Takeno, Shion, et al.
Publicado: (2023)
Bayesian Optimization with Expected Improvement: No Regret and the Choice of Incumbent
por: Wang, Jingyi, et al.
Publicado: (2025)
por: Wang, Jingyi, et al.
Publicado: (2025)
On Improved Regret Bounds In Bayesian Optimization with Gaussian Noise
por: Wang, Jingyi, et al.
Publicado: (2024)
por: Wang, Jingyi, et al.
Publicado: (2024)
No-Regret Algorithms for Safe Bayesian Optimization with Monotonicity Constraints
por: Losalka, Arpan, et al.
Publicado: (2024)
por: Losalka, Arpan, et al.
Publicado: (2024)
Bayesian Optimisation with Unknown Hyperparameters: Regret Bounds Logarithmically Closer to Optimal
por: Ziomek, Juliusz, et al.
Publicado: (2024)
por: Ziomek, Juliusz, et al.
Publicado: (2024)
Exploring Exploration in Bayesian Optimization
por: Papenmeier, Leonard, et al.
Publicado: (2025)
por: Papenmeier, Leonard, et al.
Publicado: (2025)
Exploration by Optimization with Hybrid Regularizers: Logarithmic Regret with Adversarial Robustness in Partial Monitoring
por: Tsuchiya, Taira, et al.
Publicado: (2024)
por: Tsuchiya, Taira, et al.
Publicado: (2024)
Relaxing the Additivity Constraints in Decentralized No-Regret High-Dimensional Bayesian Optimization
por: Bardou, Anthony, et al.
Publicado: (2023)
por: Bardou, Anthony, et al.
Publicado: (2023)
Regret Analysis of Posterior Sampling-Based Expected Improvement for Bayesian Optimization
por: Takeno, Shion, et al.
Publicado: (2025)
por: Takeno, Shion, et al.
Publicado: (2025)
Bayesian Optimization for Unknown Cost-Varying Variable Subsets with No-Regret Costs
por: Hoang, Vu Viet, et al.
Publicado: (2024)
por: Hoang, Vu Viet, et al.
Publicado: (2024)
Regret-Based $(ε,δ)$-optimal Stopping Criteria for Bayesian Optimization
por: Wang, Haowei, et al.
Publicado: (2026)
por: Wang, Haowei, et al.
Publicado: (2026)
Worst-Case Regret Bounds for Exploration via Randomized Value Functions
por: Russo, Daniel
Publicado: (2019)
por: Russo, Daniel
Publicado: (2019)
Optical Computing for Deep Neural Network Acceleration: Foundations, Recent Developments, and Emerging Directions
por: Pasricha, Sudeep
Publicado: (2024)
por: Pasricha, Sudeep
Publicado: (2024)
Asymptotically Optimal Regret for Black-Box Predict-then-Optimize
por: Tan, Samuel, et al.
Publicado: (2024)
por: Tan, Samuel, et al.
Publicado: (2024)
Distributed Online Convex Optimization with Compressed Communication: Optimal Regret and Applications
por: Yang, Sifan, et al.
Publicado: (2026)
por: Yang, Sifan, et al.
Publicado: (2026)
Optimal Strong Regret and Violation in Constrained MDPs via Policy Optimization
por: Stradi, Francesco Emanuele, et al.
Publicado: (2024)
por: Stradi, Francesco Emanuele, et al.
Publicado: (2024)
Ejemplares similares
-
Order-Optimal Regret in Distributed Kernel Bandits using Uniform Sampling with Shared Randomness
por: Pavlovic, Nikola, et al.
Publicado: (2024) -
Open Problem: Order Optimal Regret Bounds for Kernel-Based Reinforcement Learning
por: Vakili, Sattar
Publicado: (2024) -
Kernelized Reinforcement Learning with Order Optimal Regret Bounds
por: Vakili, Sattar, et al.
Publicado: (2023) -
Distributed Linear Bandits under Communication Constraints
por: Salgia, Sudeep, et al.
Publicado: (2022) -
Differential Privacy in Kernelized Contextual Bandits via Random Projections
por: Pavlovic, Nikola, et al.
Publicado: (2025)