Survey of Data-driven Newsvendor: Unified Analysis and Spectrum of Achievable Regrets
Fuente:
arXiv
Saved in:
| Main Authors: | Chen, Zhuoxin, Ma, Will |
|---|---|
| Format: | Preprint |
| Published: |
2024
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
What is the Value of Censored Data? An Exact Analysis for the Data-driven Newsvendor
by: Kumar, Rachitesh, et al.
Published: (2026)
by: Kumar, Rachitesh, et al.
Published: (2026)
Thompson Sampling for Repeated Newsvendor
by: Chen, Li, et al.
Published: (2025)
by: Chen, Li, et al.
Published: (2025)
The Data-Driven Censored Newsvendor Problem
by: Hssaine, Chamsi, et al.
Published: (2024)
by: Hssaine, Chamsi, et al.
Published: (2024)
From Contextual Data to Newsvendor Decisions: On the Actual Performance of Data-Driven Algorithms
by: Besbes, Omar, et al.
Published: (2023)
by: Besbes, Omar, et al.
Published: (2023)
Closing the Gaps: Optimality of Sample Average Approximation for Data-Driven Newsvendor Problems
by: Lyu, Jiameng, et al.
Published: (2024)
by: Lyu, Jiameng, et al.
Published: (2024)
Deep Generative Demand Learning for Newsvendor and Pricing
by: Gong, Shijin, et al.
Published: (2024)
by: Gong, Shijin, et al.
Published: (2024)
Achievable Fairness on Your Data With Utility Guarantees
by: Taufiq, Muhammad Faaiz, et al.
Published: (2024)
by: Taufiq, Muhammad Faaiz, et al.
Published: (2024)
Learning When to Restart: Nonstationary Newsvendor from Uncensored to Censored Demand
by: Chen, Xin, et al.
Published: (2025)
by: Chen, Xin, et al.
Published: (2025)
A Conformal Approach to Feature-based Newsvendor under Model Misspecification
by: Cao, Junyu
Published: (2024)
by: Cao, Junyu
Published: (2024)
Private Optimal Inventory Policy Learning for Feature-based Newsvendor with Unknown Demand
by: Zhao, Tuoyi, et al.
Published: (2024)
by: Zhao, Tuoyi, et al.
Published: (2024)
Decoupled Federated Learning on Long-Tailed and Non-IID data with Feature Statistics
by: Chen, Zhuoxin, et al.
Published: (2024)
by: Chen, Zhuoxin, et al.
Published: (2024)
General Identifiability and Achievability for Causal Representation Learning
by: Varıcı, Burak, et al.
Published: (2023)
by: Varıcı, Burak, et al.
Published: (2023)
Unified Framework of Distributional Regret in Multi-Armed Bandits and Reinforcement Learning
by: Lee, Harin, et al.
Published: (2026)
by: Lee, Harin, et al.
Published: (2026)
Learnability in Online Kernel Selection with Memory Constraint via Data-dependent Regret Analysis
by: Li, Junfan, et al.
Published: (2024)
by: Li, Junfan, et al.
Published: (2024)
Data-Dependent Regret Bounds for Constrained MABs
by: Genalti, Gianmarco, et al.
Published: (2025)
by: Genalti, Gianmarco, et al.
Published: (2025)
Why Most Optimism Bandit Algorithms Have the Same Regret Analysis: A Simple Unifying Theorem
by: Krishnamurthy, Vikram
Published: (2025)
by: Krishnamurthy, Vikram
Published: (2025)
Dynamic Regret Reduces to Kernelized Static Regret
by: Jacobsen, Andrew, et al.
Published: (2025)
by: Jacobsen, Andrew, et al.
Published: (2025)
Achievable distributional robustness when the robust risk is only partially identified
by: Kostin, Julia, et al.
Published: (2025)
by: Kostin, Julia, et al.
Published: (2025)
Finite-Time Regret Analysis of Retry-Aware Bandits
by: Tong, Bingkui, et al.
Published: (2026)
by: Tong, Bingkui, et al.
Published: (2026)
A Unified Framework for Generative Data Augmentation: A Comprehensive Survey
by: Chen, Yunhao, et al.
Published: (2023)
by: Chen, Yunhao, et al.
Published: (2023)
A Regret Analysis of Bilateral Trade
by: Cesa-Bianchi, Nicolò, et al.
Published: (2021)
by: Cesa-Bianchi, Nicolò, et al.
Published: (2021)
Direct Regret Optimization in Bayesian Optimization
by: Zhang, Fengxue, et al.
Published: (2025)
by: Zhang, Fengxue, et al.
Published: (2025)
Hierarchical Deep Counterfactual Regret Minimization
by: Chen, Jiayu, et al.
Published: (2023)
by: Chen, Jiayu, et al.
Published: (2023)
Data- and Variance-dependent Regret Bounds for Online Tabular MDPs
by: Li, Mingyi, et al.
Published: (2026)
by: Li, Mingyi, et al.
Published: (2026)
No Certificate for Alignment: Two Independent Impossibilities and the Pareto Frontier of Achievable Safety Guarantees
by: Agarwal, Ayushi
Published: (2026)
by: Agarwal, Ayushi
Published: (2026)
Optimizing Adaptive Experiments: A Unified Approach to Regret Minimization and Best-Arm Identification
by: Qin, Chao, et al.
Published: (2024)
by: Qin, Chao, et al.
Published: (2024)
Stochastic Predictive Analytics for Stocks in the Newsvendor Problem
by: Pury, Pedro A.
Published: (2025)
by: Pury, Pedro A.
Published: (2025)
Regret Analysis for Randomized Gaussian Process Upper Confidence Bound
by: Takeno, Shion, et al.
Published: (2024)
by: Takeno, Shion, et al.
Published: (2024)
Online-to-PAC Conversions: Generalization Bounds via Regret Analysis
by: Lugosi, Gábor, et al.
Published: (2023)
by: Lugosi, Gábor, et al.
Published: (2023)
No-Regret is not enough! Bandits with General Constraints through Adaptive Regret Minimization
by: Bernasconi, Martino, et al.
Published: (2024)
by: Bernasconi, Martino, et al.
Published: (2024)
Satisficing Regret Minimization in Bandits: Constant Rate and Light-Tailed Distribution
by: Feng, Qing, et al.
Published: (2024)
by: Feng, Qing, et al.
Published: (2024)
Eventually LIL Regret: Almost Sure $\ln\ln T$ Regret for a sub-Gaussian Mixture on Unbounded Data
by: Agrawal, Shubhada, et al.
Published: (2025)
by: Agrawal, Shubhada, et al.
Published: (2025)
Best-of-N through the Smoothing Lens: KL Divergence and Regret Analysis
by: Aminian, Gholamali, et al.
Published: (2025)
by: Aminian, Gholamali, et al.
Published: (2025)
Regret Analysis of Posterior Sampling-Based Expected Improvement for Bayesian Optimization
by: Takeno, Shion, et al.
Published: (2025)
by: Takeno, Shion, et al.
Published: (2025)
Regret Analysis of Unichain Average Reward Constrained MDPs with General Parameterization
by: Satheesh, Anirudh, et al.
Published: (2026)
by: Satheesh, Anirudh, et al.
Published: (2026)
Minimax Regret Learning for Data with Heterogeneous Subgroups
by: Mo, Weibin, et al.
Published: (2024)
by: Mo, Weibin, et al.
Published: (2024)
Data-Driven Online Model Selection With Regret Guarantees
by: Pacchiano, Aldo, et al.
Published: (2023)
by: Pacchiano, Aldo, et al.
Published: (2023)
Regret Analysis of Repeated Delegated Choice
by: Hajiaghayi, MohammadTaghi, et al.
Published: (2023)
by: Hajiaghayi, MohammadTaghi, et al.
Published: (2023)
Regret Analysis: a control perspective
by: Gibson, Travis E., et al.
Published: (2025)
by: Gibson, Travis E., et al.
Published: (2025)
Regret Analysis of Sleeping Competing Bandits
by: Uba, Shinnosuke, et al.
Published: (2026)
by: Uba, Shinnosuke, et al.
Published: (2026)
Similar Items
-
What is the Value of Censored Data? An Exact Analysis for the Data-driven Newsvendor
by: Kumar, Rachitesh, et al.
Published: (2026) -
Thompson Sampling for Repeated Newsvendor
by: Chen, Li, et al.
Published: (2025) -
The Data-Driven Censored Newsvendor Problem
by: Hssaine, Chamsi, et al.
Published: (2024) -
From Contextual Data to Newsvendor Decisions: On the Actual Performance of Data-Driven Algorithms
by: Besbes, Omar, et al.
Published: (2023) -
Closing the Gaps: Optimality of Sample Average Approximation for Data-Driven Newsvendor Problems
by: Lyu, Jiameng, et al.
Published: (2024)