8 citations · 20 across the 8 of their papers we have counts for
8 papers · 1 filter
How Do Data Science Workers Communicate Intermediate Results?
Rock Yuren Pang, Ruotong Wang, Joely Nelson +1
Data science workers increasingly collaborate on large-scale projects before communicating insights to a broader audience in the form of visualization. While prior work has modeled…
Code Code Evolution: Understanding How People Change Data Science Notebooks Over Time
Deepthi Raghunandan, Aayushi Roy, Shenzhi Shi +2
Sensemaking is the iterative process of identifying, extracting, and explaining insights from data, where each iteration is referred to as the "sensemaking loop." Although recent w…
Lodestar: Supporting Independent Learning and Rapid Experimentation Through Data-Driven Analysis Recommendations
Deepthi Raghunandan, Zhe Cui, Kartik Krishnan +5
Keeping abreast of current trends, technologies, and best practices in visualization and data analysis is becoming increasingly difficult, especially for fledgling data scientists.…
Recommendations for Visualization Recommendations: Exploring Preferences and Priorities in Public Health
Calvin Bao, Siyao Li, Sarah Flores +2
The promise of visualization recommendation systems is that analysts will be automatically provided with relevant and high-quality visualizations that will reduce the work of manua…
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…
Guided Hyperparameter Tuning Through Visualization and Inference
Hyekang Joo, Calvin Bao, Ishan Sen +2
For deep learning practitioners, hyperparameter tuning for optimizing model performance can be a computationally expensive task. Though visualization can help practitioners relate…