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Attend this computer science seminar exploring groundbreaking advances in parallel algorithms for matroid basis computation. Learn about new research that breaks the 40-year-old O(√n) barrier established by Karp, Upfal, and Wigderson, achieving an improved O(n^(3/7)) round complexity for general matroids and optimal O(n^(1/3)) rounds for partition matroids. Discover the novel matroid decomposition technique that enables these improvements and explore its applications to other classic problems like matroid intersection. The presentation covers the historical context of this fundamental problem in parallel computation, the technical innovations behind the new algorithms, and their broader implications for computational complexity theory. Gain insights into cutting-edge research at the intersection of combinatorial optimization and parallel computing, presented by Aaron Putterman from Harvard University as part of the Computer Science/Discrete Mathematics Seminar series at the Institute for Advanced Study.
