In SMT, the instability of MERT, the commonly used optimizer, is an acknowledged problem. This paper presents two methods for smoothing the MERT instability. Both exploit a set of different realizations of the same system obtained by running the optimization stage multiple times. One method averages the sets of different optimal weights; the other combines the translations generated by the vari...

Since itspublication, the seminal structuralmodelofdefault byMerton (1974) has become the workhorse for gaining insights about how firms choose their capital structure, a “bread and butter” topic for financial economists. Capital structure theory is inevitably linked to several important empirical issues such as (a) the term structure of credit spreads, (b) the level of credit spreads implied b...

While the rise of the Internet and the high speed networks made information easier to acquire, faster to exchange and more flexible to share, it also made the cybernetic attacks and crimes easier to perform, more accurate to hit the target victim and more flexible to conceal the crime evidences. Although people are in an unsafe digital environment, they often feel safe. Being aware of this fact...

High-quality parallel data is crucial for a range of multilingual applications, from tuning and evaluating machine translation systems to cross-lingual annotation projection. Unfortunately, automatically obtained parallel data (which is available in relative abundance) tends to be quite noisy. To obtain high-quality parallel data, we introduce a crowdsourcing paradigm in which workers with only...

Building a probabilistic network for a real-life domain of application is a hard and time-consuming process, which is generally performed with the help of domain experts. As the scope and, hence, the size and complexity of networks are increasing, the need for proper documentation of the elicited domain knowledge becomes apparent. To study the usefulness of ontologies for this purpose, we const...

Parameter tuning is an important problem in statistical machine translation, but surprisingly, most existing methods such as MERT, MIRA and PRO are agnostic about search, while search errors could severely degrade translation quality. We propose a searchaware framework to promote promising partial translations, preventing them from being pruned. To do so we develop two metrics to evaluate parti...

In this paper, we propose an Internet payment system which uses a payment gateway to handle the credit card payment transaction between customers, merchants and banks. To test and evaluate the payment system, we build an online travel agency called E-Travel, which simulates a real-life E-Payment application. On-line travel services including flight reservation, selling of travel accessories, to...

In this paper we describe Travatar, a forest-to-string machine translation (MT) engine based on tree transducers. It provides an open-source C++ implementation for the entire forest-to-string MT pipeline, including rule extraction, tuning, decoding, and evaluation. There are a number of options for model training, and tuning includes advanced options such as hypergraph MERT, and training of spa...

We present a unified approach to performing minimum risk training and minimum Bayes risk (MBR) decoding with BLEU in a phrase-based model. Key to our approach is the use of a Gibbs sampler that allows us to explore the entire probability distribution and maintain a strict probabilistic formulation across the pipeline. We also describe a new sampling algorithm called corpus sampling which allows...

Over the last decade, the simple instrument policy rule developed by Taylor (1993) has become a popular tool for evaluating monetary policy of central banks. As an extensive empirical analysis of the ECB’s past behaviour still seems to be in its infancy, we estimate several instrument policy reaction functions for the ECB which might shed a light on actual monetary policy in the euro area in th...