Image de couverture de livre

Incentivized Truthful Communication for Federated Bandits

Fuente: arXiv

Enregistré dans:

Détails bibliographiques
Auteurs principaux:	Wei, Zhepei, Li, Chuanhao, Ren, Tianze, Xu, Haifeng, Wang, Hongning
Format:	Preprint
Publié:	2024
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

Incentivizing Truthful Collaboration in Heterogeneous Federated Learning
par: Chakarov, Dimitar, et autres
Publié: (2024)

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

Incentive-compatible Bandits: Importance Weighting No More
par: Zimmert, Julian, et autres
Publié: (2024)

Incentivized Learning in Principal-Agent Bandit Games
par: Scheid, Antoine, et autres
Publié: (2024)

Strategic Linear Contextual Bandits
par: Buening, Thomas Kleine, et autres
Publié: (2024)

Gradient Manipulation in Distributed Stochastic Gradient Descent with Strategic Agents: Truthful Incentives with Convergence Guarantees
par: Chen, Ziqin, et autres
Publié: (2026)

Robust and Performance Incentivizing Algorithms for Multi-Armed Bandits with Strategic Agents
par: Esmaeili, Seyed A., et autres
Publié: (2023)

Incentivizing Truthful Language Models via Peer Elicitation Games
par: Chen, Baiting, et autres
Publié: (2025)

Human vs. Generative AI in Content Creation Competition: Symbiosis or Conflict?
par: Yao, Fan, et autres
Publié: (2024)

Strategic Incentivization for Locally Differentially Private Federated Learning
par: Pagoti, Yashwant Krishna, et autres
Publié: (2025)

Calibration without Ground Truth
par: Kong, Yuqing, et autres
Publié: (2026)

Federated Learning for Data Market: Shapley-UCB for Seller Selection and Incentives
par: Chen, Kongyang, et autres
Publié: (2024)

Incentivizing High-Quality Human Annotations with Golden Questions
par: Liu, Shang, et autres
Publié: (2025)

Geometry Meets Incentives: Sample-Efficient Incentivized Exploration with Linear Contexts
par: Schiffer, Benjamin, et autres
Publié: (2025)

Design of Two-Level Incentive Mechanisms for Hierarchical Federated Learning
par: Chu, Shunfeng, et autres
Publié: (2023)

Incentivized Collaboration in Active Learning
par: Cohen, Lee, et autres
Publié: (2023)

Knowledge-Free Correlated Agreement for Incentivizing Federated Learning
par: Witt, Leon, et autres
Publié: (2026)

Prior-Agnostic Incentive-Compatible Exploration
par: Ramalingam, Ramya, et autres
Publié: (2026)

Learning in Online Principal-Agent Interactions: The Power of Menus
par: Han, Minbiao, et autres
Publié: (2023)

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

Deep Incentive Design with Differentiable Equilibrium Blocks
par: Thoma, Vinzenz, et autres
Publié: (2026)

Incentivizing Exploration with Linear Contexts and Combinatorial Actions
par: Sellke, Mark
Publié: (2023)

Learning to Lead: Incentivizing Strategic Agents in the Dark
par: Wu, Yuchen, et autres
Publié: (2025)

Statistically Truthful Auctions via Acceptance Rule
par: Lotan, Roy Maor, et autres
Publié: (2024)

Hedging and Approximate Truthfulness in Traditional Forecasting Competitions
par: Monroe, Mary, et autres
Publié: (2024)

A Bayesian Incentive Mechanism for Poison-Resilient Federated Learning
par: Commey, Daniel, et autres
Publié: (2025)

Multi-Agent Combinatorial-Multi-Armed-Bandit framework for the Submodular Welfare Problem under Bandit Feedback
par: Pokhriyal, Subham, et autres
Publié: (2026)

Adversaries With Incentives: A Strategic Alternative to Adversarial Robustness
par: Ehrenberg, Maayan, et autres
Publié: (2024)

Incentivizing Honesty among Competitors in Collaborative Learning and Optimization
par: Dorner, Florian E., et autres
Publié: (2023)

Truthful mechanisms for linear bandit games with private contexts
par: Hu, Yiting, et autres
Publié: (2025)

p-Mean Regret for Stochastic Bandits
par: Krishna, Anand, et autres
Publié: (2024)

Regret Analysis of Sleeping Competing Bandits
par: Uba, Shinnosuke, et autres
Publié: (2026)

A Service-Oriented Adaptive Hierarchical Incentive Mechanism for Federated Learning
par: Cao, Jiaxing, et autres
Publié: (2025)

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

Leaderboard Incentives: Model Rankings under Strategic Post-Training
par: Chen, Yatong, et autres
Publié: (2026)

No-Regret Algorithms in non-Truthful Auctions with Budget and ROI Constraints
par: Aggarwal, Gagan, et autres
Publié: (2024)

Dynamic Matching Bandit For Two-Sided Online Markets
par: Li, Yuantong, et autres
Publié: (2022)

Adaptive Bandit Algorithms for Contextual Matching Markets
par: Lin, Shiyun, et autres
Publié: (2026)

Protocols for Verifying Smooth Strategies in Bandits and Games
par: Christ, Miranda, et autres
Publié: (2025)

T-TAMER: Provably Taming Trade-offs in ML Serving
par: Yang, Yuanyuan, et autres
Publié: (2025)