Titlebook: Algorithmic Aspects in Information and Management; 12th International C Shaojie Tang,Ding-Zhu Du,Sergiy Butenko Conference proceedings 2018

ligature

https://doi.org/10.1007/978-3-0348-6572-2. Then, we present a ./2-approximation algorithm for the graph balancing problem with .?bags; the approximation ratio is tight for . unless . and this algorithm solves the graph balancing problem with .?bags in polynomial time. In addition, we present a polynomial-time algorithm for the restricted a

好色

Shall I Compare Thee to a Wild Duck?). We compare our implementations to the Yices SMT solver [.] running linear real arithmetic (QF_LRA) and linear integer arithmetic (QF_LIA). Our experiments indicate that . is moderately superior to . in terms of time, and that . is . superior to . in terms of time. Additionally on small inputs the

異常

Factors Impacting the Label Denoising of Neural Relation Extraction,fluence the denoising effectiveness, we build a unified neural framework with word, sentence and label denoising modules for relation extraction. Then we conduct experiments to evaluate and compare these factors according to ten neural schemes. In addition, we discuss the typical cases of these fact

不容置疑

ADOPT

An Empirical Analysis of Feasibility Checking Algorithms for UTVPI Constraints,). We compare our implementations to the Yices SMT solver [.] running linear real arithmetic (QF_LRA) and linear integer arithmetic (QF_LIA). Our experiments indicate that . is moderately superior to . in terms of time, and that . is . superior to . in terms of time. Additionally on small inputs the

其他

Minimum Diameter ,-Steiner Forest,s a Steiner tree. The diameter of a .-Steiner forest is referred to as the maximum distance between two terminals of a branch. This paper studies the . and establishes the relationship between MD.SFP and the .. We first obtain a 2-approximation to AS.CP by a dual approximation algorithm and then ach

disparage

Factors Impacting the Label Denoising of Neural Relation Extraction,dress the challenge of automatically labeling large-scale training data, a distant supervision strategy is introduced to relation extraction by heuristically aligning entity pairs in plain text with the knowledge base. Unfortunately, the method is vulnerable to the noisy label problem due to the inc

output

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