VL/HCC 2022
Mon 12 - Fri 16 September 2022 Rome, Italy

This program is tentative and subject to change.

This paper describes ML Blocks, https://tinyurl.com/ml-blocks, a novel interface for training, evaluating, and deploying Tiny Machine Learning (TinyML) models. TinyML is a fast-growing field that incorporates powerful machine learning algorithms into everyday technologies such as activity trackers and Internet of Things devices. Although TinyML-capable microcontrollers are popular in computer science education, few students have had the opportunity to learn about the field because of a lack of novice-friendly ML interfaces. With ML Blocks, users assemble data sets, define, and train neural network classifiers, within one unified block interface. Users can quickly evaluate their classifiers using built-in visualization tools and then export them for use in microcontroller projects. ML Blocks makes the end-to-end development of TinyML models easier for physical computing students and tinkerers at all levels.

This program is tentative and subject to change.

Tue 13 Sep

Displayed time zone: Amsterdam, Berlin, Bern, Rome, Stockholm, Vienna change

14:00 - 15:30
Session on Human-centric ML & VisualizationsResearch Papers at San Francesco Room
14:00
30m
Talk
The Role of Expertise on Insight Generation from Visualization SequencesFull paper
Research Papers
Stephanie Rosenthal Carnegie Mellon University, Tingting Chung College of William & Mary
14:30
15m
Talk
A Crowdsourced Study of Visual Strategies for Mitigating Confirmation BiasShort paper
Research Papers
Tee Chuanromanee University of Notre Dame, Ronald Metoyer University of Notre Dame
14:45
15m
Talk
Predicting Data Scientist Stuckness During the Development of Machine Learning ClassifiersShort paper
Research Papers
Moshe Mash CMU, Shoshana Oryol CMU, Reid Simmons CMU, Stephanie Rosenthal Carnegie Mellon University
15:00
15m
Talk
ML Blocks: A Block-Based, Graphical User Interface for Creating TinyML ModelsShort paper
Research Papers
Randi Williams Massachusetts Institute of Technology, Michał Moskal Microsoft Research, Peli de Halleux Microsoft Research
15:15
15m
Talk
Human-Centric Machine Learning for Temporal Knowledge Graphs: Towards Understanding the European Alternative Fuels MarketShort paper
Research Papers
Robert Jungnickel RWTH Aachen University - Information Management in Mechanical Engineering, Aymen Gannouni RWTH Aachen University - Information Management in Mechanical Engineering, Anas Abdelrazeq RWTH Aachen University - Information Management in Mechanical Engineering, Ingrid Isenhardt RWTH Aachen University - Information Management in Mechanical Engineering