In this paper, we propose a new domain adaptation technique for neural machine translation called cost weighting, which is appropriate for adaptation scenarios in which a small in-domain data set and a large general-domain data set are available. Cost weighting incorporates a domain classifier into the neural machine translation training algorithm, using features derived from the encoder repres...

Many of the conventional similarity methods assume that molecular fragments that do not relate to biological activity carry the same weight as the important ones. One possible approach to this problem is to use the Bayesian inference network (BIN), which models molecules and reference structures as probabilistic inference networks. The relationships between molecules and reference structures in...

A primary concern when using local search methods for CNF satisfiability is how to get rid of local minimas. Among many other heuristics, Weighting by Morris (1993) and Selman and Kautz (1993) works overwhelmingly better than others (Cha and Iwama 1995). Weighting increases the weight of each clause which is unsatisfied at a local minima. This paper introduces a more sophisticated weighting str...

Various multi-criteria decision making (MCDM) methods have been proposed to solve diverse applications of decision problems. One of the MCDM methods is additive weighting-based method. However, this method is not explicitly disseminated and its applications are not-well received by many MCDM enthusiasts. This paper presents a review of the applications of simple additive weighting (SAW) and fuz...

A study was designed to compare the performance of six spatial interpolation methods to estimate soil properties at unvisited points. These methods were global mean, moving average, nearest neighbour, inverse squared distance, Laplacian smoothing splines and ordinary point kriging. These methods were also applied in combination with a choropleth map (soil map) by stratifying the area. The soil ...

The multicriteria analysis (MA) and multicriteria optimization (MO) problems are multicriteria decision making problems. In MA and MO problems several criteria are simultaneously optimized. In the general case there does not exist one alternative(solution), which optimizes all the criteria. The solution of MA or MO problem is a set of alternatives, called a set of the non-dominating or of the P...

The problem of character weighting in cladistic analysis is revisited. The finding that, in large molecular data sets, removal of third positions (with more homoplasy) decreases the number of well supported groups has been interpreted by some authors as indicating that weighting methods are unjustified. Two arguments against that interpretation are advanced. Characters that collectively determi...