most citedML-based Visualization Recommendation: Learning to Recommend Visualizations from Data

11 citations · 27 across the 5 of their papers we have counts for

collaborators

6 papers

cs.HC20214 cited

An Evaluation-Focused Framework for Visualization Recommendation Algorithms

Zehua Zeng, Phoebe Moh, Fan Du +5

Although we have seen a proliferation of algorithms for recommending visualizations, these algorithms are rarely compared with one another, making it difficult to ascertain which a…

cs.HC202110 cited

Insight-centric Visualization Recommendation

Camille Harris, Ryan A. Rossi, Sana Malik +5

Visualization recommendation systems simplify exploratory data analysis (EDA) and make understanding data more accessible to users of all skill levels by automatically generating v…

cs.IR2021

Personalized Visualization Recommendation

Xin Qian, Ryan A. Rossi, Fan Du +5

Visualization recommendation work has focused solely on scoring visualizations based on the underlying dataset and not the actual user and their past visualization feedback. These…

cs.IR202011 cited

ML-based Visualization Recommendation: Learning to Recommend Visualizations from Data

Xin Qian, Ryan A. Rossi, Fan Du +5

Visualization recommendation seeks to generate, score, and recommend to users useful visualizations automatically, and are fundamentally important for exploring and gaining insight…

cs.HC20202 cited

The Impact of Presentation Style on Human-In-The-Loop Detection of Algorithmic Bias

Po-Ming Law, Sana Malik, Fan Du +1

While decision makers have begun to employ machine learning, machine learning models may make predictions that bias against certain demographic groups. Semi-automated bias detectio…

cs.CY2020

Designing Tools for Semi-Automated Detection of Machine Learning Biases: An Interview Study

Po-Ming Law, Sana Malik, Fan Du +1

Machine learning models often make predictions that bias against certain subgroups of input data. When undetected, machine learning biases can constitute significant financial and…