The State of the Art in Enhancing Trust in Machine Learning Models with
the Use of Visualizations

The State of the Art in Enhancing Trust in Machine Learning Models with the Use of Visualizations

22 December 2022

Angelos Chatzimparmpas

R. Martins

I. Jusufi

K. Kucher

A. Kerren

Papers citing "The State of the Art in Enhancing Trust in Machine Learning Models with the Use of Visualizations"

9 / 59 papers shown

Title
CACTUS: Detecting and Resolving Conflicts in Objective Functions Subhajit Das Alex Endert 17 0 0 13 Mar 2021
Fits and Starts: Enterprise Use of AutoML and the Role of Humans in the Loop Anamaria Crisan Brittany Fiore-Gartland 14 50 0 12 Jan 2021
VIS30K: A Collection of Figures and Tables from IEEE Visualization Conference Publications Jian Chen Meng-Ying Ling Rui Li Petra Isenberg Tobias Isenberg ... Torsten Moller R. Laramee Han-Wei Shen Katharina Wünsche Qiru Wang 61 48 0 22 Dec 2020
VisEvol: Visual Analytics to Support Hyperparameter Search through Evolutionary Optimization Angelos Chatzimparmpas Rafael M. Martins Kostiantyn Kucher Andreas Kerren 16 20 0 02 Dec 2020
A Survey on ML4VIS: Applying Machine Learning Advances to Data Visualization Qianwen Wang Zhutian Chen Yong Wang Huamin Qu 18 78 0 01 Dec 2020
A Comparative Analysis of Industry Human-AI Interaction Guidelines Austin P. Wright Zijie J. Wang Haekyu Park G. Guo F. Sperrle Mennatallah El-Assady Alex Endert Daniel A. Keim Duen Horng Chau 12 29 0 22 Oct 2020
Measure Utility, Gain Trust: Practical Advice for XAI Researcher B. Pierson M. Glenski William I. N. Sealy Dustin L. Arendt 6 28 0 27 Sep 2020
Once Upon A Time In Visualization: Understanding the Use of Textual Narratives for Causality Arjun Choudhry Mandar Sharma Pramod Chundury T. Kapler Derek W. S. Gray Naren Ramakrishnan Niklas Elmqvist 11 21 0 06 Sep 2020
StackGenVis: Alignment of Data, Algorithms, and Models for Stacking Ensemble Learning Using Performance Metrics Angelos Chatzimparmpas Rafael M. Martins Kostiantyn Kucher Andreas Kerren DiffM BDL 11 73 0 04 May 2020