69 citations · 350 across the 44 of their papers we have counts for
9 papers · 1 filter
Model Compression in Practice: Lessons Learned from Practitioners Creating On-device Machine Learning Experiences
Fred Hohman, Mary Beth Kery, Donghao Ren +1
On-device machine learning (ML) promises to improve the privacy, responsiveness, and proliferation of new, intelligent user experiences by moving ML computation onto everyday perso…
Draco 2: An Extensible Platform to Model Visualization Design
Junran Yang, Péter Ferenc Gyarmati, Zehua Zeng +1
Draco introduced a constraint-based framework to model visualization design in an extensible and testable form. It provides a way to abstract design guidelines from theoretical and…
Too Many Cooks: Exploring How Graphical Perception Studies Influence Visualization Recommendations in Draco
Zehua Zeng, Junran Yang, Dominik Moritz +2
Findings from graphical perception can guide visualization recommendation algorithms in identifying effective visualization designs. However, existing algorithms use knowledge from…
Data Navigator: An accessibility-centered data navigation toolkit
Frank Elavsky, Lucas Nadolskis, Dominik Moritz
Making data visualizations accessible for people with disabilities remains a significant challenge in current practitioner efforts. Existing visualizations often lack an underlying…
Dead or Alive: Continuous Data Profiling for Interactive Data Science
Will Epperson, Vaishnavi Gorantla, Dominik Moritz +1
Profiling data by plotting distributions and analyzing summary statistics is a critical step throughout data analysis. Currently, this process is manual and tedious since analysts…
Average Estimates in Line Graphs Are Biased Toward Areas of Higher Variability
Dominik Moritz, Lace M. Padilla, Francis Nguyen +1
We investigate variability overweighting, a previously undocumented bias in line graphs, where estimates of average value are biased toward areas of higher variability in that line…
DashQL -- Complete Analysis Workflows with SQL
André Kohn, Dominik Moritz, Thomas Neumann
We present DashQL, a language that describes complete analysis workflows in self-contained scripts. DashQL combines SQL, the grammar of relational database systems, with a grammar…
Angler: Helping Machine Translation Practitioners Prioritize Model Improvements
Samantha Robertson, Zijie J. Wang, Dominik Moritz +2
Machine learning (ML) models can fail in unexpected ways in the real world, but not all model failures are equal. With finite time and resources, ML practitioners are forced to pri…
Designing Data: Proactive Data Collection and Iteration for Machine Learning
Aspen Hopkins, Fred Hohman, Luca Zappella +2
Lack of diversity in data collection has caused significant failures in machine learning (ML) applications. While ML developers perform post-collection interventions, these are tim…