Search Results for "work order"

Deep learning models have achieved impressive prediction performance but often sacrifice interpretability, a critical consideration in high-stakes domains such as healthcare or policymaking. In contrast, generalized additive models (GAMs) can maintain interpretability but often suffer from poor prediction performance due to their inability to effectively capture feature interactions. In this work, we aim to bridge this gap by using pre-trained neural language models to extract embeddings for...

Stanford Phrasal is a state-of-the-art statistical phrase-based machine translation system, written in Java. At its core, it provides much the same functionality as the core of Moses. Distinctive features include: providing an easy to use API for implementing new decoding model features, the ability to translating using phrases that include gaps (Galley et al. 2010), and conditional extraction of phrase-tables and lexical reordering models. Developed by The Natural Language Processing Group...

Strategies make up everything we do. We have thinking strategies that are effective. We have thinking strategies that are less so! It has been proven possible to secure elements of successful strategies and apply these to our training of all kinds of skills. Looking at the practices of successful people, and breaking down the parts of their effective behaviours we can teach these in order to improve particular areas of effectiveness. This is the basis of this learning and teaching strategy!

The program provides Java interface (to C++ Lemmatizer via XML-RPC) in order to perform lemmatizing in Russian, English, and German (lemma is the canonical form of a lexeme in Natural Language Processing). RussianPOSTagger could work as a module of GATE.