Adverse drug interactions are largely preventable causes of medical
acci...
We propose a stealthy and powerful backdoor attack on neural networks ba...
Software Defect Prediction aims at predicting which software modules are...
In this paper, we propose an innovative Transfer learning for Time serie...
Discovering the existence of universal adversarial perturbations had lar...
This paper presents Deepchecks, a Python library for comprehensively
val...
Anomaly detection is a well-known task that involves the identification ...
Although many studies have examined adversarial examples in the real wor...
The widespread adoption of machine learning (ML) techniques and the exte...
Despite continuous investments in data technologies, the latency of quer...
One of the challenges in the NLP field is training large classification
...
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 ...
In recent years, machine learning algorithms, and more specially, deep
l...
Improving the robustness of neural nets in regression tasks is key to th...
One of the challenging aspects of applying machine learning is the need ...
Sequential data is everywhere, and it can serve as a basis for research ...
We present the Network Traffic Generator (NTG), a framework for perturbi...
The explosion of digital data has created multiple opportunities for
org...
Automatic machine learning (AutoML) is an area of research aimed at
auto...
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...
Recommendation systems have become ubiquitous in today's online world an...
Image understanding relies heavily on accurate multi-label classificatio...
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...
Anomaly detection algorithms are often thought to be limited because the...
Adversarial examples are known to mislead deep learning models to incorr...
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...
In this paper, we present a black-box attack against API call based mach...
The WSDM Cup 2017 Triple scoring challenge is aimed at calculating and
a...
In this paper, we present a black-box attack against API call based mach...
In this work we implement a training of a Language Model (LM), using
Rec...
We present a new concept - Wikiometrics - the derivation of metrics and
...
Ensemble methods have been shown to be an effective tool for solving
mul...
Singular Value Decomposition (SVD) has been used successfully in recent ...
In this paper we examine the effect of applying ensemble learning to the...