惯性聚合 高效追踪和阅读你感兴趣的博客、新闻、科技资讯
阅读原文 在惯性聚合中打开

推荐订阅源

小众软件
小众软件
The Cloudflare Blog
V
Visual Studio Blog
G
Google Developers Blog
博客园 - Franky
The Register - Security
The Register - Security
C
CXSECURITY Database RSS Feed - CXSecurity.com
Threat Intelligence Blog | Flashpoint
Threat Intelligence Blog | Flashpoint
Cisco Talos Blog
Cisco Talos Blog
AWS News Blog
AWS News Blog
WordPress大学
WordPress大学
C
Cybersecurity and Infrastructure Security Agency CISA
H
Hacker News: Front Page
博客园 - 聂微东
aimingoo的专栏
aimingoo的专栏
有赞技术团队
有赞技术团队
NISL@THU
NISL@THU
P
Palo Alto Networks Blog
A
About on SuperTechFans
V2EX - 技术
V2EX - 技术
腾讯CDC
Project Zero
Project Zero
T
Tor Project blog
C
CERT Recently Published Vulnerability Notes
D
DataBreaches.Net
Google DeepMind News
Google DeepMind News
S
Secure Thoughts
Attack and Defense Labs
Attack and Defense Labs
H
Hackread – Cybersecurity News, Data Breaches, AI and More
N
News | PayPal Newsroom
Security Latest
Security Latest
让小产品的独立变现更简单 - ezindie.com
让小产品的独立变现更简单 - ezindie.com
Scott Helme
Scott Helme
Microsoft Security Blog
Microsoft Security Blog
阮一峰的网络日志
阮一峰的网络日志
博客园 - 叶小钗
P
Proofpoint News Feed
罗磊的独立博客
M
MIT News - Artificial intelligence
Cyber Security Advisories - MS-ISAC
Cyber Security Advisories - MS-ISAC
宝玉的分享
宝玉的分享
量子位
博客园 - 司徒正美
U
Unit 42
MyScale Blog
MyScale Blog
F
Fortinet All Blogs
Apple Machine Learning Research
Apple Machine Learning Research
Recorded Future
Recorded Future
Last Week in AI
Last Week in AI
奇客Solidot–传递最新科技情报
奇客Solidot–传递最新科技情报

cs.DS updates on arXiv.org

PAC Learning with Bandit Feedback: Sharp Sample Complexity in the Realizable Setting Algorithms with Polynomially-Improved Approximation Factors for the $2 \rightarrow q$ Norm, and Applications A computational phase transition for learning-to-sample from Ising models Covering vertices by sequential stars Fermi-Dirac machines as quantizations of neurons A Comprehensive Evaluation of Vertex Elimination Algorithms for Algorithmic Differentiation A Tight Bound on Localization of Electrical Flows Optimal Dimension-Free Sampling for Regularized Classification Reducing the Randomness in Partition Oracles for Bounded Degree Minor-Free Graphs Beyond the Half-Approximation: Fair and Efficient Online Class Matching Efficient Uniform Sampling of Surjections via their Profiles Tractable Maximization of Budgeted Phylogenetic Diversity on Networks Utilizing Node Scanwidth Fairness in Aggregation: Optimal Top-$k$ and Improved Full Ranking Learning-Augmented Online Scheduling with Parsimonious Preemption Entropy Equivalence Testing Lumberjack: Better Differentially Private Random Forests through Heavy Hitter Detection in Trees The Secretary Problem with a Stochastic Precursor Polynomial-Time Robust Multiclass Linear Classification under Gaussian Marginals Efficient Banzhaf-Based Data Valuation for $k$-Nearest Neighbors Classification Block-Sphere Vector Quantization An Approximation Algorithm for Graph Label Selection Iterative Chow Filtering for Learning with Distribution Shift Complexity of Non-Log-Concave Sampling in Fisher Information Stochastic Matching via Local Sparsification Finite Sample Bounds for Learning with Score Matching What is Learnable in Valiant's Theory of the Learnable? Provable Quantization with Randomized Hadamard Transform Min-Max Optimization Requires Exponentially Many Queries Fast and Compact Graph Cuts for the Boykov-Kolmogorov Algorithm A proximal gradient algorithm for composite log-concave sampling Adaptive Multi-Round Allocation with Stochastic Arrivals The tractability landscape of diffusion alignment: regularization, rewards, and computational primitives Mistake-Bounded Language Generation Positional LSH: Binary Block Matrix Approximation for Attention with Linear Biases Learning-Augmented Scalable Linear Assignment Problem Optimization via Neural Dual Warm-Starts A Note on Non-Negative $L_1$-Approximating Polynomials Curvature Beyond Positivity: Greedy Guarantees for Arbitrary Submodular Functions Convex Optimization with Nested Evolving Feasible Sets On the Complexity of the Matching Problem of Regular Expressions with Backreferences Simple KNN-Based Outlier Detection Achieves Robust Clustering Online Allocation with Unknown Shared Supply Equivalence of Coarse and Fine-Grained Models for Learning with Distribution Shift Accelerated Relax-and-Round for Concave Coverage Problems Contrastive Identification and Generation in the Limit Quantizing With Randomized Hadamard Transforms: Efficient Heuristic Now Proven Nearly Optimal Attention Coresets On Computing Total Variation Distance Between Mixtures of Product Distributions Exact and Approximate Algorithms for Polytree Learning Provable Accuracy Collapse in Embedding-Based Representations under Dimensionality Mismatch New Bounds for Kernel Sums via Fast Spherical Embeddings Unlearning Offline Stochastic Multi-Armed Bandits Matroid Algorithms Under Size-Sensitive Independence Oracles On the Learning Curves of Revenue Maximization Asymptotically Robust Learning-Augmented Algorithms for Preemptive FIFO Buffer Management Flashback: A Reversible Bilateral Run-Peeling Decomposition of Strings Incremental Strongly Connected Components with Predictions Characterizing Admissible Objective Functions for Hierarchical Clustering Well-Conditioned Oblivious Perturbations in Linear Space Mathematical Foundations for Peer-to-Peer Lattice Computation Graph Neural Network-Informed Predictive Flows for Faster Ford-Fulkerson and PAC-Learnability A weighted angle distance on strings Towards Universal Convergence of Backward Error in Linear System Solvers Constant-Factor Approximations for Doubly Constrained Fair k-Center, k-Median and k-Means Tight Bounds for Learning Polyhedra with a Margin Efficiency of Proportional Mechanisms in Online Auto-Bidding Advertising Skyline-First Traversal as a Control Mechanism for Multi-Criteria Graph Search Constant-Factor Approximation for the Uniform Decision Tree Limited Perfect Monotonical Surrogates constructed using low-cost recursive linkage discovery with guaranteed output Query Lower Bounds for Diffusion Sampling Early Pruning for Public Transport Routing Adapting Dijkstra for Buffers and Unlimited Transfers Exploiting Low-Rank Structure in Max-K-Cut Problems Partial Optimality in the Preordering Problem High-accuracy log-concave sampling with stochastic queries Learning to Approximate Uniform Facility Location via Graph Neural Networks Linear Regression with Unknown Truncation Beyond Gaussian Features Adaptive Power Iteration Method for Differentially Private PCA Finite and Corruption-Robust Regret Bounds in Online Inverse Linear Optimization under M-Convex Action Sets Learning Mixture Models via Efficient High-dimensional Sparse Fourier Transforms Variance Computation for Weighted Model Counting with Knowledge Compilation Approach Deterministic Coreset for Lp Subspace Online Algorithms for Repeated Optimal Stopping: Balancing Baseline Guarantees and Regret Learned Static Function Data Structures Optimal hypersurface decision trees A Perfectly Truthful Calibration Measure The Geometry of LLM Quantization: GPTQ as Babai's Nearest Plane Algorithm Best Agent Identification for General Game Playing A Faster Generalized Two-Stage Approximate Top-K Fast and Simple Densest Subgraph with Predictions Smoothed Analysis of Learning from Positive Samples Ineffectiveness for Search and Undecidability of PCSP Meta-Problems Sample-Efficient Optimization over Generative Priors via Coarse Learnability Efficient distributional regression trees learning algorithms for calibrated non-parametric probabilistic forecasts Testing Noise Assumptions of Learning Algorithms Testing Support Size More Efficiently Than Learning Histograms Sharper Bounds for Chebyshev Moment Matching, with Applications Expander Hierarchies for Normalized Cuts on Graphs Multilayer Correlation Clustering Efficient Parameter Estimation of Truncated Boolean Product Distributions Faster Hamiltonian Monte Carlo by Learning Leapfrog Scale: a self-calibrated randomized solution
The power of mediators: Price of anarchy and stability in Bayesian games with submodular social welfare
Kaito Fujii · 2025-06-03 · via cs.DS updates on arXiv.org

This paper investigates the role of mediators in Bayesian games by examining their impact on social welfare through the price of anarchy (PoA) and price of stability (PoS). Mediators can communicate with players to guide them toward equilibria of varying quality, and different communication protocols lead to a variety of equilibrium concepts collectively known as Bayes (coarse) correlated equilibria. To analyze these equilibrium concepts, we consider a general class of Bayesian games with submodular social welfare, which naturally extends valid utility games and their variant, basic utility games. These frameworks, introduced by Vetta (2002), have been developed to analyze the social welfare guarantees of equilibria in games such as competitive facility location, influence maximization, and other resource allocation problems. We provide upper and lower bounds on the PoA and PoS for a broad class of Bayes (coarse) correlated equilibria. Central to our analysis is the strategy representability gap, which measures the multiplicative gap between the optimal social welfare achievable with and without knowledge of other players' types. For monotone submodular social welfare functions, we show that this gap is $1-1/\mathrm{e}$ for independent priors and $Θ(1/\sqrt{n})$ for correlated priors, where $n$ is the number of players. These bounds directly lead to upper and lower bounds on the PoA and PoS for various equilibrium concepts, while we also derive improved bounds for specific concepts by developing smoothness arguments. Notably, we identify a fundamental gap in the PoA and PoS across different classes of Bayes correlated equilibria, highlighting essential distinctions among these concepts.