Adverse drug interactions are largely preventable causes of medical
acci...
In this paper, we propose an innovative Transfer learning for Time serie...
Anomaly detection is a well-known task that involves the identification ...
A context-aware recommender system (CARS) applies sensing and analysis o...
Testing is an important part of tackling the COVID-19 pandemic. Availabi...
The click-through rate (CTR) reflects the ratio of clicks on a specific ...
One of the challenging aspects of applying machine learning is the need ...
We present the Network Traffic Generator (NTG), a framework for perturbi...
Database activity monitoring (DAM) systems are commonly used by organiza...
Context-aware recommender systems (CARSs) apply sensing and analysis of ...
A multitude of factors are responsible for the overall quality of scient...
This paper presents a method for continuous indoor-outdoor environment
d...
The prevalence of e-learning systems and on-line courses has made educat...
Recommendation systems have become ubiquitous in today's online world an...
In real-world machine learning applications, there is a cost associated ...
In the past decade, the usage of mobile devices has gone far beyond simp...
Drug-drug interactions are preventable causes of medical injuries and of...
Before executing an attack, adversaries usually explore the victim's net...
Anomaly detection algorithms are often thought to be limited because the...
In the process of online storytelling, individual users create and consu...
Scientific writing is difficult. It is even harder for those for whom En...
A Wikipedia book (known as Wikibook) is a collection of Wikipedia articl...
The WSDM Cup 2017 Triple scoring challenge is aimed at calculating and
a...
In this work we implement a training of a Language Model (LM), using
Rec...
Singular Value Decomposition (SVD) has been used successfully in recent ...
In this paper we examine the effect of applying ensemble learning to the...