The most successful Machine Learning (ML) systems remain complex black boxes to end-
users, and even experts are often unable to understand the rationale behind their decisions …

Explainable Artificial Intelligence (XAI) has experienced a significant growth over the last few
years. This is due to the widespread application of machine learning, particularly deep …

The need for interpretable and accountable intelligent systems grows along with the
prevalence of artificial intelligence (AI) applications used in everyday life. Explainable AI …

Visual analytics for machine learning has recently evolved as one of the most exciting areas
in the field of visualization. To better identify which research topics are promising and to …

Deep learning has recently seen rapid development and received significant attention due
to its state-of-the-art performance on previously-thought hard problems. However, because …

A number of large technology companies have created code-free cloud-based platforms that
allow researchers and clinicians without coding experience to create deep learning …

Machine and deep learning have proven their utility to generate data-driven models with
high accuracy and precision. However, their non-linear, complex structures are often difficult …

We propose a framework for interactive and explainable machine learning that enables
users to (1) understand machine learning models;(2) diagnose model limitations using …

Intrusion detection systems play an important role in preventing security threats and
protecting networks from attacks. However, with the emergence of unknown attacks and …

We have recently seen many successful applications of recurrent neural networks (RNNs)
on electronic medical records (EMRs), which contain histories of patients' diagnoses …