Image de couverture de livre

Data Reliability Scoring

Fuente: arXiv

Enregistré dans:

Détails bibliographiques
Auteurs principaux:	Chen, Yiling, Feng, Shi, Kattuman, Paul, Yu, Fang-Yi
Format:	Preprint
Publié:	2025
Sujets:	Machine Learning Computer Science and Game Theory
Accès en ligne:	Acceder al recurso
Tags:	Ajouter un tag Pas de tags, Soyez le premier à ajouter un tag!

Documents similaires

Optimal Scoring Rule Design under Partial Knowledge
par: Chen, Yiling, et autres
Publié: (2021)

Carrot and Stick: Eliciting Comparison Data and Beyond
par: Chen, Yiling, et autres
Publié: (2024)

Persuading a Behavioral Agent: Approximately Best Responding and Learning
par: Chen, Yiling, et autres
Publié: (2023)

Quotation-Based Data Retention Mechanism for Data Privacy in LLM-Empowered Network Services
par: Han, Bin, et autres
Publié: (2025)

WOMAC: A Mechanism For Prediction Competitions
par: Srinivasan, Siddarth, et autres
Publié: (2025)

The Price of Ignorance: Information-Free Quotation for Data Retention in Machine Unlearning
par: Han, Bin, et autres
Publié: (2026)

Algorithmic Robust Forecast Aggregation
par: Guo, Yongkang, et autres
Publié: (2024)

Generalized Principal-Agent Problem with a Learning Agent
par: Lin, Tao, et autres
Publié: (2024)

Last-iterate Convergence Separation between Extra-gradient and Optimism in Constrained Periodic Games
par: Feng, Yi, et autres
Publié: (2024)

Temporal-Decay Shapley: A Time-Aware Data Valuation Framework for Time-Series Data
par: Pang, Chuwen, et autres
Publié: (2026)

Learning to Price Homogeneous Data
par: Chen, Keran, et autres
Publié: (2024)

Continuous-Time Analysis of Heavy Ball Momentum in Min-Max Games
par: Feng, Yi, et autres
Publié: (2025)

Is Thompson Sampling Susceptible to Algorithmic Collusion?
par: Xiong, Yi, et autres
Publié: (2024)

Data Trading Combination Auction Mechanism based on the Exponential Mechanism
par: Chen, Kongyang, et autres
Publié: (2024)

Improved Bandits in Many-to-one Matching Markets with Incentive Compatibility
par: Kong, Fang, et autres
Publié: (2024)

Learning from Random Demonstrations: Offline Reinforcement Learning with Importance-Sampled Diffusion Models
par: Fang, Zeyu, et autres
Publié: (2024)

Incentivizing Time-Aware Fairness in Data Sharing
par: Chen, Jiangwei, et autres
Publié: (2025)

DUPRE: Data Utility Prediction for Efficient Data Valuation
par: Pham, Kieu Thao Nguyen, et autres
Publié: (2025)

Do Data Valuations Make Good Data Prices?
par: Fan, Dongyang, et autres
Publié: (2025)

Towards Data Valuation via Asymmetric Data Shapley
par: Zheng, Xi, et autres
Publié: (2024)

An Instrumental Value for Data Production and its Application to Data Pricing
par: Ai, Rui, et autres
Publié: (2024)

Heterogeneous Data Game: Characterizing the Model Competition Across Multiple Data Sources
par: Xu, Renzhe, et autres
Publié: (2025)

RL-CFR: Improving Action Abstraction for Imperfect Information Extensive-Form Games with Reinforcement Learning
par: Li, Boning, et autres
Publié: (2024)

Forecasting for Swap Regret for All Downstream Agents
par: Roth, Aaron, et autres
Publié: (2024)

Learnable Mixed Nash Equilibria are Collectively Rational
par: So, Geelon, et autres
Publié: (2025)

Accelerating Nash Equilibrium Convergence in Monte Carlo Settings Through Counterfactual Value Based Fictitious Play
par: Qi, Ju, et autres
Publié: (2023)

Data-Driven Revenue Management for Air Cargo
par: Eren, Ezgi, et autres
Publié: (2024)

How Sampling Shapes LLM Alignment: From One-Shot Optima to Iterative Dynamics
par: Chen, Yurong, et autres
Publié: (2026)

Is Online Linear Optimization Sufficient for Strategic Robustness?
par: Cai, Yang, et autres
Publié: (2026)

Sample Efficient Omniprediction and Downstream Swap Regret for Non-Linear Losses
par: Lu, Jiuyao, et autres
Publié: (2025)

Market Games for Generative Models: Equilibria, Welfare, and Strategic Entry
par: Wei, Xiukun, et autres
Publié: (2026)

Distortion of AI Alignment: Does Preference Optimization Optimize for Preferences?
par: Gölz, Paul, et autres
Publié: (2025)

Optimal Pricing for Data-Augmented AutoML Marketplaces
par: Han, Minbiao, et autres
Publié: (2023)

On the Convergence of Federated Learning Algorithms without Data Similarity
par: Beikmohammadi, Ali, et autres
Publié: (2024)

Learning to Steer Learners in Games
par: Zhang, Yizhou, et autres
Publié: (2025)

Is This Predictor More Informative than Another? A Decision-Theoretical Comparison
par: Feng, Yiding, et autres
Publié: (2025)

Dynamic Pricing and Advertising with Demand Learning
par: Agrawal, Shipra, et autres
Publié: (2023)

Strategic Classification With Externalities
par: Hossain, Safwan, et autres
Publié: (2024)

Strategic Federated Learning: Application to Smart Meter Data Clustering
par: Mohamad, Hassan, et autres
Publié: (2024)

Proximal Regret and Proximal Correlated Equilibria: A New Tractable Solution Concept for Online Learning and Games
par: Cai, Yang, et autres
Publié: (2025)