Eli T. Brown
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View article: Odds and Insights: Decision Quality in Exploratory Data Analysis Under Uncertainty
Odds and Insights: Decision Quality in Exploratory Data Analysis Under Uncertainty Open
Recent studies have shown that users of visual analytics tools can have difficulty distinguishing robust findings in the data from statistical noise, but the true extent of this problem is likely dependent on both the incentive structure m…
View article: Odds and Insights: Decision Quality in Exploratory Data Analysis Under Uncertainty
Odds and Insights: Decision Quality in Exploratory Data Analysis Under Uncertainty Open
Recent studies have shown that users of visual analytics tools can have difficulty distinguishing robust findings in the data from statistical noise, but the true extent of this problem is likely dependent on both the incentive structure m…
View article: SSDBCODI: Semi-Supervised Density-Based Clustering with Outliers Detection Integrated
SSDBCODI: Semi-Supervised Density-Based Clustering with Outliers Detection Integrated Open
Clustering analysis is one of the critical tasks in machine learning. Traditionally, clustering has been an independent task, separate from outlier detection. Due to the fact that the performance of clustering can be significantly eroded b…
View article: MLUI 2021 Overview
MLUI 2021 Overview Open
The Machine Learning from User Interactions (MLUI) workshop seeks to bring together researchers to share their knowledge and build collaborations at the intersection of the Machine Learning and Visualization fields, with a focus on learnin…
View article: Multimodal Ranked Search over Integrated Repository of Radiology Data Sources
Multimodal Ranked Search over Integrated Repository of Radiology Data Sources Open
Radiology teaching files serve as a reference in the diagnosis process and as a learning resource for radiology residents. Many public teaching file data sources are available online and private in-house repositories are maintained in most…
View article: Synthetic Sampling for Multi-Class Malignancy Prediction
Synthetic Sampling for Multi-Class Malignancy Prediction Open
We explore several oversampling techniques for an imbalanced multi-label classification problem, a setting often encountered when developing models for Computer-Aided Diagnosis (CADx) systems. While most CADx systems aim to optimize classi…