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• W3184463707 abstract "Many combinatorial optimization problems are often considered intractable to solve exactly or by approximation. An example of such problem is maximum clique which -- under standard assumptions in complexity theory -- cannot be solved in sub-exponential time or be approximated within polynomial factor efficiently. We show that if a polynomial time algorithm can query informative Gaussian priors from an expert $poly(n)$ times, then a class of combinatorial optimization problems can be solved efficiently in expectation up to a multiplicative factor $epsilon$ where $epsilon$ is arbitrary constant. While our proposed methods are merely theoretical, they cast new light on how to approach solving these problems that have been usually considered intractable." @default.
• W3184463707 created "2021-08-02" @default.
• W3184463707 creator A5037597113 @default.
• W3184463707 date "2021-07-25" @default.
• W3184463707 modified "2023-09-27" @default.
• W3184463707 title "Power of human-algorithm collaboration in solving combinatorial optimization problems" @default.
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• W3184463707 hasPublicationYear "2021" @default.
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