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Multi-source AI news clustered, deduplicated, and scored 0–100 across authority, cluster strength, headline signal, and time decay.

  1. A unified complexity bound for logconcave sampling

    Researchers have developed a new, unified complexity bound for sampling logconcave distributions. This bound is nearly tight and applies to various settings, including constrained and well-conditioned densities. The analysis introduces an improved bound for the Poincaré constant of a lifted distribution, leading to more efficient convergence rates. AI