Within the vast expanse of computerized language processing, a revolutionary entity known
as Large Language Models (LLMs) has emerged, wielding immense power in its capacity to …

Language modeling studies the probability distributions over strings of texts. It is one of the
most fundamental tasks in natural language processing (NLP). It has been widely used in …

Temporal data, notably time series and spatio-temporal data, are prevalent in real-world
applications. They capture dynamic system measurements and are produced in vast …

We present a novel neural network for processing sequences. The ByteNet is a one-
dimensional convolutional neural network that is composed of two parts, one to encode the …

The easy access and exponential growth of the information available on social media
networks has made it intricate to distinguish between false and true information. The easy …

This monograph provides an overview of general deep learning methodology and its
applications to a variety of signal and information processing tasks. The application areas …

In recent years, due to the booming development of online social networks, fake news for
various commercial and political purposes has been appearing in large numbers and …

Language models have traditionally been estimated based on relative frequencies, using
count statistics that can be extracted from huge amounts of text data. More recently, it has …

Next basket recommendation is a crucial task in market basket analysis. Given a user's
purchase history, usually a sequence of transaction data, one attempts to build a …

While Deep Neural Networks (DNNs) have achieved tremendous success for large
vocabulary continuous speech recognition (LVCSR) tasks, training of these networks is …