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References
This page covers related systems / interfaces for supporting machine learning or example-centric development. For papers on specific applications of machine learning, see the Applications page.
Anind K. Dey, Raffay Hamid, Chris Beckmann, Ian Li, and Daniel Hsu. 2004. a CAPpella: programming by demonstration of context-aware applications. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (CHI '04). ACM, New York, NY, USA, 33-40. DOI=http://dx.doi.org/10.1145/985692.985697
Dan Maynes-Aminzade, Terry Winograd, and Takeo Igarashi. 2007. Eyepatch: prototyping camera-based interaction through examples. In Proceedings of the 20th annual ACM symposium on User interface software and technology (UIST '07). ACM, New York, NY, USA, 33-42. DOI=http://dx.doi.org/10.1145/1294211.1294219
Björn Hartmann, Leith Abdulla, Manas Mittal, and Scott R. Klemmer. 2007. Authoring sensor-based interactions by demonstration with direct manipulation and pattern recognition. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (CHI '07). ACM, New York, NY, USA, 145-154. DOI=http://dx.doi.org/10.1145/1240624.1240646
Daniel Ashbrook and Thad Starner. 2010. MAGIC: a motion gesture design tool. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (CHI '10). ACM, New York, NY, USA, 2159-2168. DOI=http://dx.doi.org/10.1145/1753326.1753653
Rebecca Fiebrink, Perry R. Cook, and Dan Trueman. 2011. Human model evaluation in interactive supervised learning. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (CHI '11). ACM, New York, NY, USA, 147-156. DOI=http://dx.doi.org/10.1145/1978942.1978965
Jun Kato, Sean McDirmid, and Xiang Cao. 2012. DejaVu: integrated support for developing interactive camera-based programs. In Proceedings of the 25th annual ACM symposium on User interface software and technology (UIST '12). ACM, New York, NY, USA, 189-196. DOI=http://dx.doi.org/10.1145/2380116.2380142
Kayur Patel, Naomi Bancroft, Steven M. Drucker, James Fogarty, Andrew J. Ko, and James Landay. 2010. Gestalt: integrated support for implementation and analysis in machine learning. In Proceedings of the 23nd annual ACM symposium on User interface software and technology (UIST '10). ACM, New York, NY, USA, 37-46. DOI=http://dx.doi.org/10.1145/1866029.1866038
Shahriyar Amini and Yang Li. 2013. CrowdLearner: rapidly creating mobile recognizers using crowdsourcing. In Proceedings of the 26th annual ACM symposium on User interface software and technology (UIST '13). ACM, New York, NY, USA, 163-172. DOI=http://dx.doi.org/10.1145/2501988.2502029
Adam Fourney and Michael Terry. 2012. PICL: portable in-circuit learner. In Proceedings of the 25th annual ACM symposium on User interface software and technology (UIST '12). ACM, New York, NY, USA, 569-578. DOI=http://dx.doi.org/10.1145/2380116.2380188
Bullock, J., Momeni, A. (2015). ml.lib: Robust, Cross-platform, Open-source Machine Learning for Max and Pure Data. NIME 2015. https://nime2015.lsu.edu/proceedings/201/0201-paper.pdf
Shahriar Nirjon, Robert F. Dickerson, Philip Asare, Qiang Li, Dezhi Hong, John A. Stankovic, Pan Hu, Guobin Shen, and Xiaofan Jiang. 2013. Auditeur: a mobile-cloud service platform for acoustic event detection on smartphones. In Proceeding of the 11th annual international conference on Mobile systems, applications, and services (MobiSys '13). ACM, New York, NY, USA, 403-416. DOI=http://dx.doi.org/10.1145/2462456.2464446
Designing for Effective End-User Interaction with Machine Learning, Salem Amershi, dissertation, University of Washington 2012: http://research.microsoft.com/en-us/um/people/samershi/papers/amershi_Dissertation_2012.pdf
Todd Kulesza, Margaret Burnett, Weng-Keen Wong, and Simone Stumpf. 2015. Principles of Explanatory Debugging to Personalize Interactive Machine Learning. In Proceedings of the 20th International Conference on Intelligent User Interfaces (IUI '15). ACM, New York, NY, USA, 126-137. DOI=http://dx.doi.org/10.1145/2678025.2701399
Simone Stumpf, Vidya Rajaram, Lida Li, Weng-Keen Wong, Margaret Burnett, Thomas Dietterich, Erin Sullivan, and Jonathan Herlocker. 2009. Interacting meaningfully with machine learning systems: Three experiments. Int. J. Hum.-Comput. Stud. 67, 8 (August 2009), 639-662. DOI=http://dx.doi.org/10.1016/j.ijhcs.2009.03.004
Jerry Fails and Dan Olsen. 2003. A design tool for camera-based interaction. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (CHI '03). ACM, New York, NY, USA, 449-456. DOI=http://dx.doi.org/10.1145/642611.642690
Human-Centred Machine Learning Workshop at CHI 2016: summary of themes.
Stephen Oney and Joel Brandt. 2012. Codelets: linking interactive documentation and example code in the editor. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (CHI '12). ACM, New York, NY, USA, 2697-2706. DOI=http://dx.doi.org/10.1145/2207676.2208664
Joel Brandt, Mira Dontcheva, Marcos Weskamp, and Scott R. Klemmer. 2010. Example-centric programming: integrating web search into the development environment. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (CHI '10). ACM, New York, NY, USA, 513-522. DOI=http://dx.doi.org/10.1145/1753326.1753402
Björn Hartmann, Loren Yu, Abel Allison, Yeonsoo Yang, and Scott R. Klemmer. 2008. Design as exploration: creating interface alternatives through parallel authoring and runtime tuning. In Proceedings of the 21st annual ACM symposium on User interface software and technology (UIST '08). ACM, New York, NY, USA, 91-100. DOI=http://dx.doi.org/10.1145/1449715.1449732
Brian Lee, Savil Srivastava, Ranjitha Kumar, Ronen Brafman, and Scott R. Klemmer. 2010. Designing with interactive example galleries. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (CHI '10). ACM, New York, NY, USA, 2257-2266. DOI=http://dx.doi.org/10.1145/1753326.1753667
Ranjitha Kumar, Jerry O. Talton, Salman Ahmad, and Scott R. Klemmer. 2011. Bricolage: example-based retargeting for web design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (CHI '11). ACM, New York, NY, USA, 2197-2206. DOI=http://dx.doi.org/10.1145/1978942.1979262 (This is something of a contrasting approach, turning existing finished products into templates rather than requiring explicit template / example authoring.)
Martin, Fred G. "Ideal and real systems: A study of notions of control in undergraduates who design robots." In Y. Kafai and M. Resnick (Eds.), Constructionism in Practice: Rethinking the Roles of Technology in Learning. 1996.
Microsoft Azure Learning Studio
ml.lib: GRT for Max and Pure Data
What are other good real-time machine learning libraries / frameworks (e.g. Python, Javascript, Java)?