Archive

Great Innovative Ideas

Great Innovative Ideas are a way to showcase the exciting new research and ideas generated by the computing community.

Cyrus Shahabi headshot

Privacy-Preserving Inference of Social Relationships from Location Data

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We envision an extensible framework dubbed Privacy-Preserving Location Analytics and Computation Environment (Private-PLACE), which enables social relationship studies by analyzing individually generated location data. Private-PLACE utilizes an untrusted server and computes several building blocks to support various social relationship studies, without disclosing location information to the server and other untrusted parties.

Philip Guo headshot

Python Tutor

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The following Great Innovative Idea is from Philip J. Guo, Assistant Professor in the Department of Computer Science at the University of Rochester. Philip recently attended the Computing Community Consortium Computer-Aided Personalized Education Workshop in Washington, DC and presented his work on Python Tutor. The Innovative Idea One of the most fundamental skills to develop when learning […]

Nikolaus Correll Picture

Materials that Couple Sensing, Actuation, Computation, and Communication

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The following Great Innovative Idea is from Nikolaus Correll, Assistant Professor in the Department of Computer Science at the University of Colorado at Boulder, about his paper with University of Colorado at Boulder doctoral student Andy McEvoy on Materials that couple sensing, actuation, computation, and communication.  The Innovative Idea Advances in polymers and miniaturization of computing devices allow us to […]

Stefanie Tellex headshot

Acquiring Object Experiences at Scale

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The following Great Innovative Idea is from John Oberlin, Maria Meier, Tim Kraska, and Stefanie Tellex in the Computer Science Department at Brown University. Their Acquiring Object Experiences at Scale was one of the winners at the Computing Community Consortium (CCC) sponsored Blue Sky Ideas Track Competition at the AAAI-RSS Special Workshop on the 50th […]

Sergey Levine, Chelsea Finn, Trevor Darrell, and Pieter Abbeel headshots

End-to-End Training of Deep Visuomotor Policies

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The following Great Innovative Idea is from Sergey Levine, Chelsea Finn, Trevor Darrell, and Pieter Abbeel in the Electrical Engineering and Computer Sciences (EECS) Department at the University of California Berkeley. Their End-to-End Training of Deep Visuomotor Policies paper was one of the winners at the Computing Community Consortium (CCC) sponsored Blue Sky Ideas Track Competition at the AAAI-RSS Special […]

Michela Milano and Pascal Van Hentenryck headshot

Emerging Architectures for Global System Science

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The following Great Innovative Idea is from Michela Milano at the University of Bologna-Italy and Pascal Van Hentenryck from NICTA Optimisation Research Group and the University of Michigan. Their Emerging Architectures for Global System Science paper was one of the winners at the Computing Community Consortium (CCC) sponsored Blue Sky Ideas Conference Track at the 29th Association for the Advancement of Artificial Intelligence […]

Speculative Reprogramming

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The following Great Innovative Idea is from Marc Palyart at the University of British Columbia, Gail C. Murphy at the Univeristy of British Columbia, Emerson Murphy-Hill at NC State University, and Xavier Blanc at Bordeaux University. Their Speculative Reprogramming paper won third place at the Computing Community Consortium (CCC) sponsored Blue Sky Ideas Conference Track series at the 22nd ACM SIGSOFT International Symposium on Foundations of Software Engineering (FSE), November 16-22, 2014 in Hong Kong. […]

Sebastian Elbaum and David S. Rosenblum

Known Unknowns: Testing in the Presence of Uncertainty

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The following Great Innovative Idea is from Sebastian Elbaum, Professor of Computer Science and Engineering at the University of Nebraska-Lincoln and David S. Rosenblum, Dean of the School of Computing at the National University of Singapore.

Their paper Known Unknowns: Testing in the Presence of Uncertainty won second place at the Computing Community Consortium (CCC) sponsored Blue Sky Ideas Conference Track series at the 22nd ACM SIGSOFT International Symposium on Foundations of Software Engineering (FSE), November 16-22, 2014 in Hong Kong.

Jerry Zhu giving a lecture.

Machine Teaching

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Machine teaching is machine learning turned upside down: it is about finding the optimal (e.g. the smallest) training set. For example, consider a “student” who runs the Support Vector Machine learning algorithm. Imagine a teacher who wants to teach the student a specific target hyperplane in some feature space (never mind how the teacher got this hyperplane in the first place). The teacher constructs a training set D=(x1,y1) … (xn, yn), where xi is a feature vector and yi a class label, to train the student. What is the smallest training set that will make the student learn the target hyperplane?

The following Great Innovative Idea is from Dr. Xiaojin (Jerry) Zhu, Associate Professor of Computer Science at University of Wisconsin-Madison. Zhu’s paper Machine Teaching: an Inverse Problem to Machine Learning and an Approach Toward Optimal Education won the Computing Community Consortium (CCC) sponsored Blue Sky Ideas Conference Track series at the 29th Association for the Advancement of Artificial Intelligence (AAAI) Conference on Artificial Intelligence (AAAI-15), January 25-30, 2015 in Austin, Texas.
Dr. Marian Petre and Dr. Daniela Damian

Development Methodology

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The following Great Innovative Idea is from Dr. Marian Petre, Professor of Computer Science at Open University, UK and Dr. Daniela Damian, Professor of Software Engineering at the University of Victoria, Canada.

Petre and Damian received First Place for their paper Methodology and Culture: Drivers of Mediocrity in Software Engineering? at the Computing Community Consortium (CCC) sponsored Blue Sky Ideas Conference Track series at the 22nd ACM SIGSOFT International Symposium on Foundations of Software Engineering (FSE), November 16-22, 2014 in Hong Kong.