The field of machine translation (MT), the automatic translation of written text from one
natural language into another, has experienced a major paradigm shift in recent years …

Multi-document summarization (MDS) is an effective tool for information aggregation that
generates an informative and concise summary from a cluster of topic-related documents …

The field of explainable artificial intelligence (XAI) is gaining increasing importance in recent
years. As a consequence, several surveys have been published to explore the current state …

Neural networks are a family of powerful machine learning models and this book focuses on
their application to natural language data. The first half of the book (Parts I and II) covers the …

The principal submatrix localization problem deals with recovering a K× K principal
submatrix of elevated mean µ in a large n× n symmetric matrix subject to additive standard …

Many natural language processing tasks, including the most advanced ones, routinely start
by several basic processing steps–tokenization and segmentation, most likely also POS …

Pre-trained word embeddings learned from unlabeled text have become a standard
component of neural network architectures for NLP tasks. However, in most cases, the …

Microblogging platforms are an ideal place for spreading rumors and automatically
debunking rumors is a crucial problem. To detect rumors, existing approaches have relied …

We introduce a method to train Binarized Neural Networks (BNNs)-neural networks with
binary weights and activations at run-time. At training-time the binary weights and activations …

Neural Machine Translation (NMT) is an end-to-end learning approach for automated
translation, with the potential to overcome many of the weaknesses of conventional phrase …