I tiakina i:
| Ngā kaituhi matua: | Lazzaro, Joseph, Pike-Burke, Ciara |
|---|---|
| Hōputu: | Preprint |
| I whakaputaina: |
2025
|
| Ngā marau: | |
| Urunga tuihono: | https://arxiv.org/abs/2507.08994 |
| Ngā Tūtohu: |
Tāpirihia he Tūtohu
Kāore He Tūtohu, Me noho koe te mea tuatahi ki te tūtohu i tēnei pūkete!
|
Ngā tūemi rite
Fixed-Budget Change Point Identification in Piecewise Constant Bandits
mā: Lazzaro, Joseph, me ētahi atu.
I whakaputaina: (2025)
mā: Lazzaro, Joseph, me ētahi atu.
I whakaputaina: (2025)
Locally Differentially Private Thresholding Bandits
mā: Barbara, Annalisa, me ētahi atu.
I whakaputaina: (2025)
mā: Barbara, Annalisa, me ētahi atu.
I whakaputaina: (2025)
QuACK: A Multipurpose Queuing Algorithm for Cooperative $k$-Armed Bandits
mā: Howson, Benjamin, me ētahi atu.
I whakaputaina: (2024)
mā: Howson, Benjamin, me ētahi atu.
I whakaputaina: (2024)
The Sample Complexity of Multiple Change Point Identification under Bandit Feedback
mā: Graf, Maximilian, me ētahi atu.
I whakaputaina: (2026)
mā: Graf, Maximilian, me ētahi atu.
I whakaputaina: (2026)
Learning Fair And Effective Points-Based Rewards Programs
mā: Hssaine, Chamsi, me ētahi atu.
I whakaputaina: (2025)
mā: Hssaine, Chamsi, me ētahi atu.
I whakaputaina: (2025)
When and why randomised exploration works (in linear bandits)
mā: Abeille, Marc, me ētahi atu.
I whakaputaina: (2025)
mā: Abeille, Marc, me ētahi atu.
I whakaputaina: (2025)
Sample-Efficiency in Multi-Batch Reinforcement Learning: The Need for Dimension-Dependent Adaptivity
mā: Johnson, Emmeran, me ētahi atu.
I whakaputaina: (2023)
mā: Johnson, Emmeran, me ētahi atu.
I whakaputaina: (2023)
Optimal Best Arm Identification with Fixed Confidence in Restless Bandits
mā: Karthik, P. N., me ētahi atu.
I whakaputaina: (2023)
mā: Karthik, P. N., me ētahi atu.
I whakaputaina: (2023)
Stochastic Shortest Path with Sparse Adversarial Costs
mā: Johnson, Emmeran, me ētahi atu.
I whakaputaina: (2025)
mā: Johnson, Emmeran, me ētahi atu.
I whakaputaina: (2025)
Optimal Best-Arm Identification under Fixed Confidence with Multiple Optima
mā: Truong, Lan V.
I whakaputaina: (2025)
mā: Truong, Lan V.
I whakaputaina: (2025)
On the necessity of adaptive regularisation:Optimal anytime online learning on $\boldsymbol{\ell_p}$-balls
mā: Johnson, Emmeran, me ētahi atu.
I whakaputaina: (2025)
mā: Johnson, Emmeran, me ētahi atu.
I whakaputaina: (2025)
Bandit Pareto Set Identification: the Fixed Budget Setting
mā: Kone, Cyrille, me ētahi atu.
I whakaputaina: (2023)
mā: Kone, Cyrille, me ētahi atu.
I whakaputaina: (2023)
Constrained Pareto Set Identification with Bandit Feedback
mā: Kone, Cyrille, me ētahi atu.
I whakaputaina: (2025)
mā: Kone, Cyrille, me ētahi atu.
I whakaputaina: (2025)
Fair Best Arm Identification with Fixed Confidence
mā: Russo, Alessio, me ētahi atu.
I whakaputaina: (2024)
mā: Russo, Alessio, me ētahi atu.
I whakaputaina: (2024)
Fixed Confidence Best Arm Identification in the Bayesian Setting
mā: Jang, Kyoungseok, me ētahi atu.
I whakaputaina: (2024)
mā: Jang, Kyoungseok, me ētahi atu.
I whakaputaina: (2024)
Risk-Averse Best Arm Set Identification with Fixed Budget and Fixed Confidence
mā: Nonaga, Shunta, me ētahi atu.
I whakaputaina: (2025)
mā: Nonaga, Shunta, me ētahi atu.
I whakaputaina: (2025)
A Finite Time Analysis of Thompson Sampling for Bayesian Optimization with Preferential Feedback
mā: Lazzaro, Joseph, me ētahi atu.
I whakaputaina: (2026)
mā: Lazzaro, Joseph, me ētahi atu.
I whakaputaina: (2026)
Fixed-Budget Constrained Best Arm Identification in Grouped Bandits
mā: Mukherjee, Raunak, me ētahi atu.
I whakaputaina: (2026)
mā: Mukherjee, Raunak, me ētahi atu.
I whakaputaina: (2026)
Multi-thresholding Good Arm Identification with Bandit Feedback
mā: Jiang, Xuanke, me ētahi atu.
I whakaputaina: (2025)
mā: Jiang, Xuanke, me ētahi atu.
I whakaputaina: (2025)
The Cost of Learning under Multiple Change Points
mā: Gafni, Tomer, me ētahi atu.
I whakaputaina: (2026)
mā: Gafni, Tomer, me ētahi atu.
I whakaputaina: (2026)
Multiclass Online Learnability under Bandit Feedback
mā: Raman, Ananth, me ētahi atu.
I whakaputaina: (2023)
mā: Raman, Ananth, me ētahi atu.
I whakaputaina: (2023)
Fixed-Confidence Best Arm Identification with Decreasing Variance
mā: Roychowdhury, Tamojeet, me ētahi atu.
I whakaputaina: (2025)
mā: Roychowdhury, Tamojeet, me ētahi atu.
I whakaputaina: (2025)
Fixed Budget is No Harder Than Fixed Confidence in Best-Arm Identification up to Logarithmic Factors
mā: Balagopalan, Kapilan, me ētahi atu.
I whakaputaina: (2026)
mā: Balagopalan, Kapilan, me ētahi atu.
I whakaputaina: (2026)
Robust Pareto Set Identification with Contaminated Bandit Feedback
mā: Korkmaz, İlter Onat, me ētahi atu.
I whakaputaina: (2022)
mā: Korkmaz, İlter Onat, me ētahi atu.
I whakaputaina: (2022)
Optimal Multi-Objective Best Arm Identification with Fixed Confidence
mā: Chen, Zhirui, me ētahi atu.
I whakaputaina: (2025)
mā: Chen, Zhirui, me ētahi atu.
I whakaputaina: (2025)
Prior-Dependent Allocations for Bayesian Fixed-Budget Best-Arm Identification in Structured Bandits
mā: Nguyen, Nicolas, me ētahi atu.
I whakaputaina: (2024)
mā: Nguyen, Nicolas, me ētahi atu.
I whakaputaina: (2024)
Learning Markov Decision Processes under Fully Bandit Feedback
mā: Zhuo, Zhengjia, me ētahi atu.
I whakaputaina: (2026)
mā: Zhuo, Zhengjia, me ētahi atu.
I whakaputaina: (2026)
Nearest Neighbour with Bandit Feedback
mā: Pasteris, Stephen, me ētahi atu.
I whakaputaina: (2023)
mā: Pasteris, Stephen, me ētahi atu.
I whakaputaina: (2023)
Optimal High-Probability Regret for Online Convex Optimization with Two-Point Bandit Feedback
mā: Ye, Haishan
I whakaputaina: (2026)
mā: Ye, Haishan
I whakaputaina: (2026)
Efficient Algorithms for Logistic Contextual Slate Bandits with Bandit Feedback
mā: Goyal, Tanmay, me ētahi atu.
I whakaputaina: (2025)
mā: Goyal, Tanmay, me ētahi atu.
I whakaputaina: (2025)
Improved Online Confidence Bounds for Multinomial Logistic Bandits
mā: Lee, Joongkyu, me ētahi atu.
I whakaputaina: (2025)
mā: Lee, Joongkyu, me ētahi atu.
I whakaputaina: (2025)
Lipschitz Bandits with Stochastic Delayed Feedback
mā: Liu, Zhongxuan, me ētahi atu.
I whakaputaina: (2025)
mā: Liu, Zhongxuan, me ētahi atu.
I whakaputaina: (2025)
Queueing Matching Bandits with Preference Feedback
mā: Kim, Jung-hun, me ētahi atu.
I whakaputaina: (2024)
mā: Kim, Jung-hun, me ētahi atu.
I whakaputaina: (2024)
Graph Feedback Bandits with Similar Arms
mā: Qi, Han, me ētahi atu.
I whakaputaina: (2024)
mā: Qi, Han, me ētahi atu.
I whakaputaina: (2024)
Nonparametric Kernel Clustering with Bandit Feedback
mā: Thuot, Victor, me ētahi atu.
I whakaputaina: (2026)
mā: Thuot, Victor, me ētahi atu.
I whakaputaina: (2026)
Cascading Bandits With Feedback
mā: Prakash, R Sri, me ētahi atu.
I whakaputaina: (2025)
mā: Prakash, R Sri, me ētahi atu.
I whakaputaina: (2025)
Optimal Clustering with Bandit Feedback
mā: Yang, Junwen, me ētahi atu.
I whakaputaina: (2022)
mā: Yang, Junwen, me ētahi atu.
I whakaputaina: (2022)
Stochastic $k$-Submodular Bandits with Full Bandit Feedback
mā: Nie, Guanyu, me ētahi atu.
I whakaputaina: (2024)
mā: Nie, Guanyu, me ētahi atu.
I whakaputaina: (2024)
Fixed Point Neural Acceleration and Inverse Surrogate Model for Battery Parameter Identification
mā: Cheon, Hojin, me ētahi atu.
I whakaputaina: (2025)
mā: Cheon, Hojin, me ētahi atu.
I whakaputaina: (2025)
Multi-Agent Combinatorial-Multi-Armed-Bandit framework for the Submodular Welfare Problem under Bandit Feedback
mā: Pokhriyal, Subham, me ētahi atu.
I whakaputaina: (2026)
mā: Pokhriyal, Subham, me ētahi atu.
I whakaputaina: (2026)
Ngā tūemi rite
-
Fixed-Budget Change Point Identification in Piecewise Constant Bandits
mā: Lazzaro, Joseph, me ētahi atu.
I whakaputaina: (2025) -
Locally Differentially Private Thresholding Bandits
mā: Barbara, Annalisa, me ētahi atu.
I whakaputaina: (2025) -
QuACK: A Multipurpose Queuing Algorithm for Cooperative $k$-Armed Bandits
mā: Howson, Benjamin, me ētahi atu.
I whakaputaina: (2024) -
The Sample Complexity of Multiple Change Point Identification under Bandit Feedback
mā: Graf, Maximilian, me ētahi atu.
I whakaputaina: (2026) -
Learning Fair And Effective Points-Based Rewards Programs
mā: Hssaine, Chamsi, me ētahi atu.
I whakaputaina: (2025)