Word alignment for long distance language pairs is problematic in state-of-the-art phrasebased statistical machine translation. Linguistically motivated reordering models have been widely studied to conquer this challenge. One of the most popular and effective methods is called pre-reordering, where words in sentences from the source language are re-arranged with the objective to resemble the w...

Lexicalized and hierarchical reordering models use relative frequencies of fully lexicalized phrase pairs to learn phrase reordering distributions. This results in unreliable estimation for infrequent phrase pairs which also tend to be longer phrases. There are some smoothing techniques used to smooth the distributions in these models. But these techniques are unable to address the similarities...

Botnets are a significant source of abusive messaging (spam, phishing, etc) and other types of malicious traffic. A promising approach to help mitigate botnet-generated traffic is signal analysis of transport-layer (i.e. TCP/IP) characteristics, e.g. timing, packet reordering, congestion, and flow-control. Prior work [4] shows that machine learning analysis of such traffic features on an SMTP M...

This paper analyzes the performance of a genetic algorithm that utilizes tournament selection, one-point crossover, and a reordering operator. A model is proposed to describe the combined effect of the reordering operator and tournament selection, and the numerical solutions are presented as well. Pairwise, s-ary, and probabilistic tournament selection are all included in the proposed model. It...

In this paper, we propose novel extensions of hierarchical phrase-based systems with a discriminative lexicalized reordering model. We compare different feature sets for the discriminative reordering model and investigate combinations with three types of non-lexicalized reordering rules which are added to the hierarchical grammar in order to allow for more reordering flexibility during decoding...

This paper introduces new technique for efficient calculation of different Shannon information measures which operates Binary Decision Diagrams (BDDs). We offer an algorithm of BDD reordering which demonstrates the improvement of the obtaining outcomes over the existing reordering approaches. The technique and the reordering algorithm have been implemented, and the results on circuits’ benchmar...

Variable reordering is the main approach to minimize the size of Ordered Binary Decision Diagrams. But despite the huge effort spent, up to now, to design different reordering heuristics, their performance often does not meet the needs of the applications. In many OBDD-based computations, the time cost for reordering dominates the time spent by the computa-

System architecture, experimental settings and experimental results of the EHR group for the WAT2016 tasks are described. We participate in six tasks: en-ja, zh-ja, JPCzh-ja, JPCko-ja, HINDENen-hi and HINDENhi-ja. Although the basic architecture of our systems is PBSMT with reordering, several techniques are conducted. Especially, the system for the HINDENhi-ja task with pivoting by English use...

Structured syntactic knowledge is important for phrase reordering. This paper proposes using convolution tree kernel over source parse tree to model structured syntactic knowledge for BTG-based phrase reordering in the context of statistical machine translation. Our study reveals that the structured syntactic features over the source phrases are very effective for BTG constraint-based phrase re...

Reordering is one source of error in statistical machine translation (SMT). This paper extends the study of the statistical machine reordering (SMR) approach, which uses the powerful techniques of the SMT systems to solve reordering problems. Here, the novelties yield in: (1) using the SMR approach in a SMT phrase-based system, (2) adding a feature function in the SMR step, and (3) analyzing th...