Artificial intelligence in cyber security: research advances, challenges, and opportunities
In recent times, there have been attempts to leverage artificial intelligence (AI) techniques in
a broad range of cyber security applications. Therefore, this paper surveys the existing …
a broad range of cyber security applications. Therefore, this paper surveys the existing …
A review of user interface design for interactive machine learning
JJ Dudley, PO Kristensson - ACM Transactions on Interactive Intelligent …, 2018 - dl.acm.org
Interactive Machine Learning (IML) seeks to complement human perception and intelligence
by tightly integrating these strengths with the computational power and speed of computers …
by tightly integrating these strengths with the computational power and speed of computers …
Disaster City Digital Twin: A vision for integrating artificial and human intelligence for disaster management
This paper presents a vision for a Disaster City Digital Twin paradigm that can:(i) enable
interdisciplinary convergence in the field of crisis informatics and information and …
interdisciplinary convergence in the field of crisis informatics and information and …
What do we need to build explainable AI systems for the medical domain?
Artificial intelligence (AI) generally and machine learning (ML) specifically demonstrate
impressive practical success in many different application domains, eg in autonomous …
impressive practical success in many different application domains, eg in autonomous …
Digital transformation in smart farm and forest operations needs human-centered AI: challenges and future directions
The main impetus for the global efforts toward the current digital transformation in almost all
areas of our daily lives is due to the great successes of artificial intelligence (AI), and in …
areas of our daily lives is due to the great successes of artificial intelligence (AI), and in …
Explainable AI: the new 42?
Explainable AI is not a new field. Since at least the early exploitation of CS Pierce's
abductive reasoning in expert systems of the 1980s, there were reasoning architectures to …
abductive reasoning in expert systems of the 1980s, there were reasoning architectures to …
From machine learning to explainable AI
A Holzinger - 2018 world symposium on digital intelligence for …, 2018 - ieeexplore.ieee.org
The success of statistical machine learning (ML) methods made the field of Artificial
Intelligence (AI) so popular again, after the last AI winter. Meanwhile deep learning …
Intelligence (AI) so popular again, after the last AI winter. Meanwhile deep learning …
Reinforcement learning approaches in social robotics
This article surveys reinforcement learning approaches in social robotics. Reinforcement
learning is a framework for decision-making problems in which an agent interacts through …
learning is a framework for decision-making problems in which an agent interacts through …
Interactive machine learning: experimental evidence for the human in the algorithmic loop: A case study on Ant Colony Optimization
Recent advances in automatic machine learning (aML) allow solving problems without any
human intervention. However, sometimes a human-in-the-loop can be beneficial in solving …
human intervention. However, sometimes a human-in-the-loop can be beneficial in solving …
The need to approximate the use-case in clinical machine learning
The availability of smartphone and wearable sensor technology is leading to a rapid
accumulation of human subject data, and machine learning is emerging as a technique to …
accumulation of human subject data, and machine learning is emerging as a technique to …