Matrix Factorization is a successful approach for generating an effective recommender
system. However, most existing matrix factorization methods suffer from the sparsity and cold …

Visual media, in today's world, has swept across most forms of day to day communication. In
the paradigm of generative modelling, restricted Boltzmann machines (RBMs) are used to …

Destination prediction is known as an important problem for many location based services
(LBSs). Existing solutions generally apply probabilistic models or neural network models to …

Regarded as one of the common cancers, the prostate cancer is a main reason harming the
health of senile men, especially in Europe and the United States. In China, with increasing of …

Recommender system has received tremendous attention and has been studied by scholars
in recent years due to its wide applications in different domains. With the in‐depth study and …

Abstract Convolutional Neural Networks (CNNs) have become the main solution for image
classification tasks in different applications. Although several CNN architectures are …

This article discusses the analysis of Spotify's music data and the generation of
recommendations based on subscribers' preferences. The recommendation algorithm …

Recommendation systems are achieving great success in e-Commerce applications, during
a live interaction with a customer; recommendation system may apply different techniques to …

With more and more Deep Neural Network (DNN) models are publicly available on model
sharing platforms (eg, HuggingFace), model reuse has become a promising way in practice …

In recent years, researchers have commonly employed assistant tasks to enhance the
training phase of the few-shot classification models. Several methods have been proposed …