research
∙
06/09/2021
Practical Machine Learning Safety: A Survey and Primer
The open-world deployment of Machine Learning (ML) algorithms in safety-...
share
research
∙
06/07/2021
Multi-task Transformation Learning for Robust Out-of-Distribution Detection
Detecting out-of-distribution (OOD) samples plays a key role in open-wor...
research
∙
07/24/2020
Machine Learning Explanations to Prevent Overtrust in Fake News Detection
Combating fake news and misinformation propagation is a challenging task...
research
∙
12/20/2019
Practical Solutions for Machine Learning Safety in Autonomous Vehicles
Autonomous vehicles rely on machine learning to solve challenging tasks ...
research
∙
07/08/2019
XFake: Explainable Fake News Detector with Visualizations
In this demo paper, we present the XFake system, an explainable fake new...
research
∙
05/19/2019
Predicting Model Failure using Saliency Maps in Autonomous Driving Systems
While machine learning systems show high success rate in many complex ta...
research
∙
04/04/2019
Open Issues in Combating Fake News: Interpretability as an Opportunity
Combating fake news needs a variety of defense methods. Although rumor d...
research
∙
11/29/2018
Combating Fake News with Interpretable News Feed Algorithms
Nowadays, artificial intelligence algorithms are used for targeted and p...
research
∙
11/29/2018
Combating Fake News with Interpretable News Feed Algorithm
Nowadays, artificial intelligence algorithms are used for targeted and p...
research
∙
11/28/2018
A Survey of Evaluation Methods and Measures for Interpretable Machine Learning
The need for interpretable and accountable intelligent system gets sensi...
research
∙
01/16/2018
ProvThreads: Analytic Provenance Visualization and Segmentation
Our work aims to generate visualizations to enable meta-analysis of anal...
research
∙
01/16/2018
Analytic Provenance Datasets: A Data Repository of Human Analysis Activity and Interaction Logs
We present an analytic provenance data repository that can be used to st...
research
∙
01/16/2018