activity
20182025
most citedExplainable AI for Intelligence Augmentation in Multi-Domain Operations

6 citations · 8 across the 3 of their papers we have counts for

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Showing 2018Show all

5 papers · 1 filter

cs.SI2018

Learning Features of Network Structures Using Graphlets

Kun Tu, Jian Li, Don Towsley +2

Networks are fundamental to the study of complex systems, ranging from social contacts, message transactions, to biological regulations and economical networks. In many realistic a…

cs.CY2018

Hows and Whys of Artificial Intelligence for Public Sector Decisions: Explanation and Evaluation

Alun Preece, Rob Ashelford, Harry Armstrong +1

Evaluation has always been a key challenge in the development of artificial intelligence (AI) based software, due to the technical complexity of the software artifact and, often, i…

cs.AI2018

Stakeholders in Explainable AI

Alun Preece, Dan Harborne, Dave Braines +2

There is general consensus that it is important for artificial intelligence (AI) and machine learning systems to be explainable and/or interpretable. However, there is no general c…

cs.SI2018

Network Classification in Temporal Networks Using Motifs

Kun Tu, Jian Li, Don Towsley +2

Network classification has a variety of applications, such as detecting communities within networks and finding similarities between those representing different aspects of the rea…

cs.AI2018

Interpretable to Whom? A Role-based Model for Analyzing Interpretable Machine Learning Systems

Richard Tomsett, Dave Braines, Dan Harborne +2

Several researchers have argued that a machine learning system's interpretability should be defined in relation to a specific agent or task: we should not ask if the system is inte…