No-regret algorithms for online $k$-submodular maximization
We present a polynomial time algorithm for online maximization of $k$-submodular maximization. For online (nonmonotone) $k$-submodular maximization, our algorithm achieves a tight approximate factor in an approximate regret. For online monotone $k$-submodular maximization, our approximate-regret matches to the best-known approximation ratio, which is tight asymptotically as $k$ tends to infinity. Our approach is based on the Blackwell approachability theorem and online linear optimization.
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Tasuku Soma (add twitter)
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07/15/18 09:31PM
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tasusu: AISTATS 2019に単著論文が採択されました👍k劣モジュラ関数のオンライン最大化に対して,O(√T) 近似regretを達成するアルゴリズムを作りました.論文はこちら https://t.co/cuwTGzWMSD
ComputerPapers: No-regret algorithms for online $k$-submodular maximization. https://t.co/ZChpxxQMeX
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