1,070 research outputs found

    Detecting Simultaneous Integer Relations for Several Real Vectors

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    An algorithm which either finds an nonzero integer vector m{\mathbf m} for given tt real nn-dimensional vectors x1,...,xt{\mathbf x}_1,...,{\mathbf x}_t such that xiTm=0{\mathbf x}_i^T{\mathbf m}=0 or proves that no such integer vector with norm less than a given bound exists is presented in this paper. The cost of the algorithm is at most O(n4+n3logλ(X)){\mathcal O}(n^4 + n^3 \log \lambda(X)) exact arithmetic operations in dimension nn and the least Euclidean norm λ(X)\lambda(X) of such integer vectors. It matches the best complexity upper bound known for this problem. Experimental data show that the algorithm is better than an already existing algorithm in the literature. In application, the algorithm is used to get a complete method for finding the minimal polynomial of an unknown complex algebraic number from its approximation, which runs even faster than the corresponding \emph{Maple} built-in function.Comment: 10 page

    Front-to-End Bidirectional Heuristic Search with Near-Optimal Node Expansions

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    It is well-known that any admissible unidirectional heuristic search algorithm must expand all states whose ff-value is smaller than the optimal solution cost when using a consistent heuristic. Such states are called "surely expanded" (s.e.). A recent study characterized s.e. pairs of states for bidirectional search with consistent heuristics: if a pair of states is s.e. then at least one of the two states must be expanded. This paper derives a lower bound, VC, on the minimum number of expansions required to cover all s.e. pairs, and present a new admissible front-to-end bidirectional heuristic search algorithm, Near-Optimal Bidirectional Search (NBS), that is guaranteed to do no more than 2VC expansions. We further prove that no admissible front-to-end algorithm has a worst case better than 2VC. Experimental results show that NBS competes with or outperforms existing bidirectional search algorithms, and often outperforms A* as well.Comment: Accepted to IJCAI 2017. Camera ready version with new timing result
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