Recommender Systems (RS) have proven to be effective tools to help users overcome
information overload, and significant advances have been made in the field over the past …

In this paper, we present a hybrid real-time incremental stochastic gradient descent (RI-
SGD) updating technique for implicit feedback matrix factorization (MF) recommendation …

As the most widely used OS on earth, Android is heavily targeted by malicious hackers.
Though much work has been done on detecting Android malware, hackers are becoming …

With the massive explosion of machine learning in our day-to-day life, incremental and
adaptive learning has become a major topic, crucial to keep up-to-date and improve …

Cognitive diagnosis, aiming at providing an approach to reveal the proficiency level of
learners on knowledge concepts, plays an important role in intelligent education area and …

Matrix factorization is one of the fundamental approaches of recommender systems. With the
popular L 2 loss, learning models tend to overfit significantly deviated predictions. However …

Online incremental models for recommendation are nowadays pervasive in both the industry
and the academia. However, there is not yet a standard evaluation methodology for the …

Conversational recommendation is ubiquitous in e-commerce, while three-way
recommendation provides friendly choices for service providers and users. However, their …

Factorization models have been successfully applied to the recommendation problems and
have significant impact to both academia and industries in the field of Collaborative Filtering …

Developing machine learning models that outperform the existing ones has been defined as
the main goal of researchers and industry experts. In this context, the carbon footprint …