New research details information complexity in broadcast model coin problem

A new research paper published on arXiv explores the coin problem within the broadcast model, focusing on distributed testing of specific probability distributions. The study characterizes information complexity and identifies optimal protocols based on different channel types, including a novel mixed Hellinger--Jensen--Shannon inequality. The findings have applications in deriving lower bounds for multi-pass streaming settings and testing arbitrary discrete distributions. AI

IMPACT This theoretical research in information complexity may inform future advancements in distributed AI systems and data analysis.

RANK_REASON The cluster contains a single academic paper published on arXiv detailing theoretical computer science research. [lever_c_demoted from research: ic=1 ai=0.4]

Read on arXiv stat.ML →

• alphaXiv
• arXiv
• Ber(alpha)
• Ber(beta)
• Broadcast Model
• coin problem
• Hugging Face
• information theory
• Mixed Hellinger--Jensen--Shannon inequality
• Z Channel

• paper
• other

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