Group sparse CNNs for question classification with answer sets
Mingbo Ma, Liang Huang, et al.
ACL 2017
Most existing techniques for combining multiple alignment tables can combine only two alignment tables at a time, and are based on heuristics (Och and Ney, 2003), (Koehn et al., 2003). In this paper, we propose a novel mathematical formulation for combining an arbitrary number of alignment tables using their power mean. The method frames the combination task as an optimization problem, and finds the optimal alignment lying between the intersection and union of multiple alignment tables by optimizing the parameter p: the affinely extended real number defining the order of the power mean function. The combination approach produces better alignment tables in terms of both F-measure and BLEU scores.
Mingbo Ma, Liang Huang, et al.
ACL 2017
Bowen Zhou, Bing Xiang, et al.
SSST 2008
Mo Yu, Wenpeng Yin, et al.
ACL 2017
Jia Cui, Yonggang Deng, et al.
ASRU 2009