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Private Sequential Learning
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What this work says
Outgoing claims: the papers this work cites, builds on, or argues with.
inferredcites →https://doi.org/10.1007/11681878_14openalex-snapshot
Calibrating Noise to Sensitivity in Private Data Analysis
inferredcites →https://doi.org/10.1109/focs.2012.87openalex-snapshot
The Privacy of the Analyst and the Power of the State
inferredcites →https://doi.org/10.1109/sfcs.1997.646125openalex-snapshot
Replication is not needed: single database, computationally-private information retrieval
inferredcites →https://doi.org/10.1109/tifs.2017.2779108openalex-snapshot
Hypothesis Testing Under Mutual Information Privacy Constraints in the High Privacy Regime
inferredcites →https://doi.org/10.1109/tit.1963.1057832openalex-snapshot
Sequential transmission using noiseless feedback
inferredcites →https://doi.org/10.1126/science.aaa9375openalex-snapshot
The reusable holdout: Preserving validity in adaptive data analysis
inferredcites →https://doi.org/10.1137/120861898openalex-snapshot
Bisection Search with Noisy Responses
inferredcites →https://doi.org/10.1145/1993636.1993743openalex-snapshot
Privacy-preserving statistical estimation with optimal convergence rates
inferredcites →https://doi.org/10.1145/2450142.2450148openalex-snapshot
A learning theory approach to noninteractive database privacy
inferredcites →https://doi.org/10.1145/2746539.2746580openalex-snapshot
Preserving Statistical Validity in Adaptive Data Analysis
inferredcites →https://doi.org/10.1198/jasa.2009.tm08651openalex-snapshot
A Statistical Framework for Differential Privacy
inferredcites →https://doi.org/10.1287/opre.2017.1682openalex-snapshot
Delay-Predictability Trade-offs in Reaching a Secret Goal
inferredcites →https://doi.org/10.1561/0400000042openalex-snapshot
The Algorithmic Foundations of Differential Privacy
What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
inferred← citeshttps://doi.org/10.2139/ssrn.4724820openalex-extracted
Homomorphic Encrypted Revenue Management
inferred← citeshttps://doi.org/10.2139/ssrn.4729530openalex-extracted
Finding the Best Arm Privately in Unimodal Bandits
inferred← citeshttps://doi.org/10.1007/978-3-030-94676-0_18openalex-snapshot
The Platform Design Problem
inferred← citeshttps://doi.org/10.1016/j.fmre.2024.11.028openalex-snapshot
Data-driven and people-centric operations: Research opportunities in retail operations
inferred← citeshttps://doi.org/10.1109/ijcnn64981.2025.11229290openalex-snapshot
Position Paper: Rethinking Privacy in RL for Sequential Decision-making in the Age of LLMs
inferred← citeshttps://doi.org/10.1109/isit45174.2021.9517915openalex-snapshot
Resolution Limits of Non-Adaptive 20 Questions Estimation for Multiple Targets
inferred← citeshttps://doi.org/10.1109/lcsys.2024.3406543openalex-snapshot
Structured Reinforcement Learning for Incentivized Stochastic Covert Optimization
inferred← citeshttps://doi.org/10.1109/ojcsys.2022.3207108openalex-snapshot
Differentially Private Algorithms for Statistical Verification of Cyber-Physical Systems
inferred← citeshttps://doi.org/10.1109/tit.2022.3166074openalex-snapshot
Resolution Limits of Non-Adaptive 20 Questions Search for Multiple Targets
inferred← citeshttps://doi.org/10.1109/tit.2022.3203989openalex-snapshot
Learner-Private Convex Optimization
inferred← citeshttps://doi.org/10.1287/mnsc.2021.4129openalex-snapshot
Privacy-Preserving Dynamic Personalized Pricing with Demand Learning
inferred← citeshttps://doi.org/10.1287/msom.2023.0271openalex-snapshot
Privacy-Preserving Personalized Recommender Systems
inferred← citeshttps://doi.org/10.2139/ssrn.3700474openalex-snapshot
Privacy-Preserving Dynamic Personalized Pricing with Demand Learning
inferred← citeshttps://doi.org/10.2139/ssrn.3875606openalex-snapshot
Private Genetic Genealogy Search
inferred← citeshttps://doi.org/10.2139/ssrn.3919807openalex-snapshot
Differential Privacy in Personalized Pricing with Nonparametric Demand Models
inferred← citeshttps://doi.org/10.2139/ssrn.5219878openalex-snapshot
Privacy-Preserving Data-Driven Inventory Management
inferred← citeshttps://doi.org/10.23919/acc55779.2023.10156637openalex-snapshot
Statistical Verification of Traffic Systems with Expected Differential Privacy
inferred← citeshttps://doi.org/10.3934/naco.2024041openalex-snapshot
Controlling stochastic gradient descent using stochastic approximation for robust distributed optimization
inferred← citeshttps://doi.org/10.48550/arxiv.2009.12920openalex-snapshot
Privacy-Preserving Dynamic Personalized Pricing with Demand Learning
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