43 citations · 288 across the 47 of their papers we have counts for
8 papers · 1 filter
Helix: Holistic Optimization for Accelerating Iterative Machine Learning
Doris Xin, Stephen Macke, Litian Ma +3
Machine learning workflow development is a process of trial-and-error: developers iterate on workflows by testing out small modifications until the desired accuracy is achieved. Un…
ShapeSearch: A Flexible and Efficient System for Shape-based Exploration of Trendlines
Tarique Siddiqui, Zesheng Wang, Paul Luh +2
Identifying trendline visualizations with desired patterns is a common and fundamental data exploration task. Existing visual analytics tools offer limited flexibility and expressi…
Helix: Accelerating Human-in-the-loop Machine Learning
Doris Xin, Litian Ma, Jialin Liu +3
Data application developers and data scientists spend an inordinate amount of time iterating on machine learning (ML) workflows -- by modifying the data pre-processing, model train…
Accelerating Human-in-the-loop Machine Learning: Challenges and Opportunities
Doris Xin, Litian Ma, Jialin Liu +3
Development of machine learning (ML) workflows is a tedious process of iterative experimentation: developers repeatedly make changes to workflows until the desired accuracy is atta…
How Developers Iterate on Machine Learning Workflows -- A Survey of the Applied Machine Learning Literature
Doris Xin, Litian Ma, Shuchen Song +1
Machine learning workflow development is anecdotally regarded to be an iterative process of trial-and-error with humans-in-the-loop. However, we are not aware of quantitative evide…
The Importance of Norm Regularization in Linear Graph Embedding: Theoretical Analysis and Empirical Demonstration
Yihan Gao, Chao Zhang, Jian Peng +1
Learning distributed representations for nodes in graphs is a crucial primitive in network analysis with a wide spectrum of applications. Linear graph embedding methods learn such…
Characterizing Scalability Issues in Spreadsheet Software using Online Forums
Kelly Mack, John Lee, Kevin Chang +2
In traditional usability studies, researchers talk to users of tools to understand their needs and challenges. Insights gained via such interviews offer context, detail, and backgr…
Towards a Theory of Data-Diff: Optimal Synthesis of Succinct Data Modification Scripts
Tana Wattanawaroon, Stephen Macke, Aditya Parameswaran
This paper addresses the Data-Diff problem: given a dataset and a subsequent version of the dataset, find the shortest sequence of operations that transforms the dataset to the sub…