Cover Image

What is the Value of Censored Data? An Exact Analysis for the Data-driven Newsvendor

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Kumar, Rachitesh, Mouchtaki, Omar
Format:	Preprint
Published:	2026
Subjects:	Machine Learning
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

From Contextual Data to Newsvendor Decisions: On the Actual Performance of Data-Driven Algorithms
by: Besbes, Omar, et al.
Published: (2023)

Prior-Independent Bidding Strategies for First-Price Auctions
by: Kumar, Rachitesh, et al.
Published: (2025)

The Data-Driven Censored Newsvendor Problem
by: Hssaine, Chamsi, et al.
Published: (2024)

Beyond IID: data-driven decision-making in heterogeneous environments
by: Besbes, Omar, et al.
Published: (2022)

Survey of Data-driven Newsvendor: Unified Analysis and Spectrum of Achievable Regrets
by: Chen, Zhuoxin, et al.
Published: (2024)

Learning When to Restart: Nonstationary Newsvendor from Uncensored to Censored Demand
by: Chen, Xin, et al.
Published: (2025)

Strategically-Robust Learning Algorithms for Bidding in First-Price Auctions
by: Kumar, Rachitesh, et al.
Published: (2024)

What Data Enables Optimal Decisions? An Exact Characterization for Linear Optimization
by: Bennouna, Omar, et al.
Published: (2025)

Online Generalized-mean Welfare Maximization: Achieving Near-Optimal Regret from Samples
by: Yang, Zongjun, et al.
Published: (2026)

Thompson Sampling for Repeated Newsvendor
by: Chen, Li, et al.
Published: (2025)

Closing the Gaps: Optimality of Sample Average Approximation for Data-Driven Newsvendor Problems
by: Lyu, Jiameng, et al.
Published: (2024)

Doubly Robust Conformalized Survival Analysis with Right-Censored Data
by: Sesia, Matteo, et al.
Published: (2024)

Spatial Supply Repositioning with Censored Demand Data
by: Jiang, Hansheng, et al.
Published: (2025)

Neural Networks for Censored Expectile Regression Based on Data Augmentation
by: Cao, Wei, et al.
Published: (2025)

Deep Generative Demand Learning for Newsvendor and Pricing
by: Gong, Shijin, et al.
Published: (2024)

In-Context Learning for Data-Driven Censored Inventory Control
by: Mukherjee, Sohom, et al.
Published: (2026)

Benchmarking Observational Studies with Experimental Data under Right-Censoring
by: Demirel, Ilker, et al.
Published: (2024)

Learning Robust Treatment Rules for Censored Data
by: Cui, Yifan, et al.
Published: (2024)

A Conformal Approach to Feature-based Newsvendor under Model Misspecification
by: Cao, Junyu
Published: (2024)

Deep Partially Linear Transformation Model for Right-Censored Survival Data
by: Yin, Junkai, et al.
Published: (2024)

Learning High-dimensional Gaussians from Censored Data
by: Bhattacharyya, Arnab, et al.
Published: (2025)

Private Optimal Inventory Policy Learning for Feature-based Newsvendor with Unknown Demand
by: Zhao, Tuoyi, et al.
Published: (2024)

ICODEN: Ordinary Differential Equation Neural Networks for Interval-Censored Data
by: Wang, Haoling, et al.
Published: (2026)

Interpretable Deep Regression Models with Interval-Censored Failure Time Data
by: Yuan, Changhui, et al.
Published: (2025)

Self-Consistent Equation-guided Neural Networks for Censored Time-to-Event Data
by: Kim, Sehwan, et al.
Published: (2025)

Censoring-Aware Tree-Based Reinforcement Learning for Estimating Dynamic Treatment Regimes with Censored Outcomes
by: Paul, Animesh Kumar, et al.
Published: (2025)

Heterogeneous Treatment Effect in Time-to-Event Outcomes: Harnessing Censored Data with Recursively Imputed Trees
by: Meir, Tomer, et al.
Published: (2025)

Linking Across Data Granularity: Fitting Multivariate Hawkes Processes to Partially Interval-Censored Data
by: Calderon, Pio, et al.
Published: (2021)

Exact Recovery in the Data Block Model
by: Asadi, Amir R., et al.
Published: (2026)

Machine Learning for Two-Sample Testing under Right-Censored Data: A Simulation Study
by: Philonenko, Petr, et al.
Published: (2024)

Deep Copula-Based Survival Analysis for Dependent Censoring with Identifiability Guarantees
by: Zhang, Weijia, et al.
Published: (2023)

Censor Dependent Variational Inference
by: Liu, Chuanhui, et al.
Published: (2025)

Random Survival Forest for Censored Functional Data
by: Romano, Elvira, et al.
Published: (2024)

Exact Unlearning of Finetuning Data via Model Merging at Scale
by: Kuo, Kevin, et al.
Published: (2025)

Exactly Computing do-Shapley Values
by: Witter, R. Teal, et al.
Published: (2026)

Adaptive Experimentation for Censored Survival Outcomes
by: Wang, Yuxin, et al.
Published: (2026)

Bayesian Active Learning for Censored Regression
by: Hüttel, Frederik Boe, et al.
Published: (2024)

What's the next frontier for Data-centric AI? Data Savvy Agents
by: Seedat, Nabeel, et al.
Published: (2025)

Exact Certification of Data-Poisoning Attacks Using Mixed-Integer Programming
by: Sosnin, Philip, et al.
Published: (2026)

Steinmetz Neural Networks for Complex-Valued Data
by: Venkatasubramanian, Shyam, et al.
Published: (2024)