Distributed word embeddings have shown superior performances in numerous Natural Language Processing (NLP) tasks. However, their performances vary significantly across different tasks, implying that the word embeddings learnt by those methods capture complementary aspects of lexical semantics. Therefore, we believe that it is important to combine the existing word embeddings to produce more acc...

This study discusses a method for quantitative quality assessment for the simplification of linear features. Considering the multi-scale nature of linear features, this paper combines the improved Douglas–Peucker method without threshold and the multiway tree model to construct a weighted hierarchical linear feature representation model called the Douglas–Peucker Multiway Tree (DMC-tree). Subse...

We consider Ising models on graphs that converge locally to trees. Examples include random regular graphs with bounded degree and uniformly random graphs with bounded average degree. We prove that the ‘cavity’ prediction for the limiting free energy per spin is correct for any temperature and external field. Further, local marginals can be approximated by iterating a set of mean field (cavity) ...

Different genes often have different phylogenetic histories. Even within regions having the same phylogenetic history, the mutation rates often vary. We investigate the prospects of phylogenetic reconstruction when all the characters are generated from the same tree topology, but the branch lengths vary (with possibly different tree shapes). Furthering work of Kolaczkowski and Thornton (2004, N...

directional felling of trees plays a key role in reducing of damages to forest residual trees and can also facilitate skidding. the aim of this study was presents a practical linear model for estimation of tree falling direction error in an uneven-aged mixed stand in northern forests of iran. to conduct the study a number of 95 trees of four species fagus orientalis lipsky, carpinus betulus l.,...

Time series forecasting in highly nonlinear and chaotic systems is a challenging research area with a variety of applications in economics, environmental sciences and various fields of engineering. This paper presents a novel Locally Quadratic Fuzzy Neural Model (LQFNM) to forecast the behavior of highly nonlinear and chaotic time series. It is based on the idea of approximating a nonlinear fun...

This paper presents a data envelopment analysis (DEA) model combined with Bootstrapping to assess performance of one of the Data mining Algorithms. We applied a two-step process for performance productivity analysis of insurance branches within a case study. First, using a DEA model, the study analyzes the productivity of eighteen decision-making units (DMUs). Using a Malmquist index, DEA deter...

A major problem for the learning of Bayesian networks (BNs) is the exponential number of parameters needed for conditional prob­ ability tables. Recent research reduces this complexity by modeling local structure in the probability tables. We examine the use of log-linear local models. While log-linear models in this context are not new (Whit­ taker, 1990; Buntine, 1991; Neal, 1992; Heck­ erman...

We consider multistage stochastic linear optimization problems combining joint dynamic probabilistic constraints with hard constraints. We develop a method for projecting decision rules onto hard constraints of wait-and-see type. We establish the relation between the original (infinite-dimensional) problem and approximating problems working with projections from different subclasses of decision...