The workshop will have 4 panel sessions, each on a different theme. Each panel will be comprised of 4 participants giving a 15 minute talk, followed by a 30 minute plenary discussion. There will also be a poster session in the breaks.

The workshop will be in room 210H.
Videos of the Talks are available here

We will have a shared google docs folder to make notes on the workshop

9:00 Interacting with Machine Learning

Human-Centered and Interactive: Expanding the Impact of Topic Models
Alison Smith, Tak Yeon Lee, Forough Poursabzi-Sangdeh, Jordan Boyd-Graber, Niklas Elmqvist, Kevin Seppi and Leah Findlater
Usability Challenges underlying Bicluster Interaction for Sensemaking
Maoyuan Sun, Peng Mi, Hao Wu, Chris North and Naren Ramakrishnan
Human-Machine-Learner Interaction: The Best of Both Worlds
Eli T. Brown, Remco Chang and Alex Endert
Debugging Machine Learning
Gabriel Cadamuro, Ran Gilad-Bachrach and Xiaojin Zhu

10:30 Coffee and Posters

11:00 Applications

Machine Learning in Expressive Gestural Interaction
Baptiste Caramiaux
Methods for Estimating User State from Real-time fNIRS Data
Samuel Hincks, Daniel Afergan and Robert Jacob
Motion Data and Machine Learning: Prototyping and Evaluation
Thierry Ravet Ravet, Joëlle Tilmanne Tilmanne, Nicolas d’Alessandro and Sohaib Laraba
Interactive Active Learning for Self-Tracking in mHealth
Scott Cambo and Darren Gergle

12:30 Lunch

13:30 Visualisation and Interpretation

Interpretable Machine Learning: Lessons from Topic Modeling
Michael Paul
Supporting User Interaction with Machine Learning through Interactive Visualizations
Jules Françoise, Frédéric Bevilacqua and Thecla Schiphorst
Explanations Considered Harmful? User Interactions with Machine Learning Systems
Simone Stumpf, Adrian Bussone and Dympna O’Sullivan
Designing Usable Interactive Visual Analytics Tools for Dimension Reduction
Jessica Zeitz Self, Xinran Hu, Leanna House, Scotland Leman and Chris North

 15:00 Coffee and Posters

15:30 Beyond labelling

Resolvable vs. Irresolvable Ambiguity: A New Hybrid Framework for Dealing with Uncertain Ground Truth
Mike Schaekermann, Edith Law, Alex C. Williams and William Callaghan.
Computational Narrative Intelligence: A Human-Centered Goal for Artificial Intelligence
Mark Riedl
Challenges of Applying Machine Learning to Qualitative Coding
Nan-Chen Chen, Rafal Kocielnik, Margaret Drouhard, Vanessa Peña-Araya, Jina Suh, Keting Cen, Xiangyi Zheng and Cecilia R. Aragon
Research Prospects in the Design and Evaluation of Interactive Evolutionary Systems for Art and Science
Nadia Boukhelifa, Anastasia Bezerianos, Alberto Tonda and Evelyne Lutton.


Optical Music Recognition with Human Labeled Constraints
Raphael Christopher, Liang Chen, Yucong Jiang, Rong Jin and Erik Stolterman
The Moving Target in Creative Interactive Machine Learning
Mark Cartwright and Bryan Pardo
Exploring Effective Decision Making through Human-Centered and Computational Intelligence Methods
Kyungsik Han, Kristin Cook and Patrick C. Shih
“Why Should I Trust You?'”: Explaining the Predictions of Any Classifier
Marco Tulio Ribeiro, Sameer Singh and Carlos Guestrin
Learning Layout Design: Challenges and Opportunities
Janin Koch, Daryl Weir and Antti Oulasvirta
Bridging Machine Learning and Real World Complexities with Interaction Design
Qian Yang
Data literacy to support human-centred machine learning
Annika Wolff, Daniel Gooch and Gerd Kortuem
Can Machine-Learning Apply to Musical Ensembles?
Charles Martin and Henry Gardner
Towards Crowd-Assisted Data Mining
Sai Gouravajhala, Danai Koutra and Walter Lasecki