Machine Learning
Interaction-level support for collaborative learning: AlgoBlock—an open programming language
CSCL '95 The first international conference on Computer support for collaborative learning
Tangible bits: towards seamless interfaces between people, bits and atoms
Proceedings of the ACM SIGCHI Conference on Human factors in computing systems
Phidgets: easy development of physical interfaces through physical widgets
Proceedings of the 14th annual ACM symposium on User interface software and technology
A design tool for camera-based interaction
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
iStuff: a physical user interface toolkit for ubiquitous computing environments
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
The calder toolkit: wired and wireless components for rapidly prototyping interactive devices
DIS '04 Proceedings of the 5th conference on Designing interactive systems: processes, practices, methods, and techniques
Physical Prototyping with Smart-Its
IEEE Pervasive Computing
From turtles to Tangible Programming Bricks: explorations in physical language design
Personal and Ubiquitous Computing
Reflective physical prototyping through integrated design, test, and analysis
UIST '06 Proceedings of the 19th annual ACM symposium on User interface software and technology
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
CueFlik: interactive concept learning in image search
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Enabling nonexpert construction of basic sensor-based systems
ACM Transactions on Computer-Human Interaction (TOCHI)
Electronics as material: littleBits
Proceedings of the 3rd International Conference on Tangible and Embedded Interaction
The WEKA data mining software: an update
ACM SIGKDD Explorations Newsletter
MAGIC: a motion gesture design tool
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Gestalt: integrated support for implementation and analysis in machine learning
UIST '10 Proceedings of the 23nd annual ACM symposium on User interface software and technology
A rapid prototyping tool for interactive device development
HCII'11 Proceedings of the 14th international conference on Human-computer interaction: design and development approaches - Volume Part I
Electronics as material: littleBits
Proceedings of the Sixth International Conference on Tangible, Embedded and Embodied Interaction
.NET gadgeteer: a platform for custom devices
Pervasive'12 Proceedings of the 10th international conference on Pervasive Computing
Touch & activate: adding interactivity to existing objects using active acoustic sensing
Proceedings of the 26th annual ACM symposium on User interface software and technology
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This paper introduces the PICL, the portable in-circuit learner. The PICL explores the possibility of providing standalone, low-cost, programming-by-demonstration machine learning capabilities to circuit prototyping. To train the PICL, users attach a sensor to the PICL, demonstrate example input, then specify the desired output (expressed as a voltage) for the given input. The current version of the PICL provides two learning modes, binary classification and linear regression. To streamline training and also make it possible to train on highly transient signals (such as those produced by a camera flash or a hand clap), the PICL includes a number of input inferencing techniques. These techniques make it possible for the PICL to learn with as few as one example. The PICL's behavioural repertoire can be expanded by means of various output adapters, which serve to transform the output in useful ways when prototyping. Collectively, the PICL's capabilities allow users of systems such as the Arduino or littleBits electronics kit to quickly add basic sensor-based behaviour, with little or no programming required.