Author Archives: jkh6

From Denoising to Compressed Sensing

C. A. Metzler, A. Maleki, and R. G. Baraniuk, “From Denoising to Compressed Sensing,” July 2014.  arXiv version Abstract:  A denoising algorithm seeks to remove perturbations or errors from a signal. The last three decades have seen extensive research devoted … Continue reading

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Adaptive Textbook Project Launched

Rice University-based nonprofit OpenStax, which has already provided free textbooks to hundreds of thousands of college students, today announced a $9 million effort supported by the Laura and John Arnold Foundation to develop free, digital textbooks capable of delivering personalized … Continue reading

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Thomson Reuters’ Highly Cited Researcher for 2014

Richard Baraniuk was one of 3,215 researchers in the sciences and social sciences who authored papers that ranked among the top 1% most cited for their subject field and year of publication in Thomson Reuters’ academic citation indexing and search … Continue reading

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Free Texbooks at Lower Prices

Rice University-based publisher OpenStax College today announced a distribution partnership with NACSCORP, a subsidiary of the National Association of College Stores (NACS), that will allow the nonprofit publisher to drop prices on all its print textbooks and distribute them to … Continue reading

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Removing ‘Barriers’ to Education through Free College Textbooks

Removing ‘barriers’ to education through free college textbooks By Emanuella Grinberg, CNN April 18, 2014 Link to article

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When in Doubt, SWAP!

D. Vats and R. G. Baraniuk, “Swapping Variables for High-Dimensional Sparse Regression with Correlated Measurements,” NIPS 2013, journal preprint 2014. Abstract: We consider the high-dimensional sparse linear regression problem of accurately estimating a sparse vector using a small number of … Continue reading

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On the PaTh to Greatness

D. Vats and R. G. Baraniuk, “Path Thresholding: Asymptotically Tuning-Free High-Dimensional Sparse Regression,” in Proceedings of the 17th International Conference on Artificial Intelligence and Statistics (AISTATS), 2014 Abstract: In this paper, we address the challenging problem of selecting tuning parameters … Continue reading

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Improved STEM Learning with Cognitive Science

A. C. Butler, E. J. Marsh, J. P. Slavinsky, and R. G. Baraniuk, “Integrating Cognitive Science and Technology Improves Learning in a STEM Classroom,” Educational Psychology Review, March 2014. Preprint version of the paper Press release Abstract:  The most effective … Continue reading

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Everybody Must Get STOne

T. Goldstein, L. Xu, K. F. Kelly, and R. G. Baraniuk, “The STOne Transform: Multi-Resolution Image Enhancement and Real-Time Compressive Video,” 2013. Abstract:  Compressive sensing enables the reconstruction of high-resolution signals from under-sampled data. While compressive methods simplify data acquisition, … Continue reading

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Personalized Learning Workshop 2 April 2014

THE SCIENCE OF LEARNING:  Bridging the Laboratory-Classroom Divide Revitalizing education at all levels and in all subject areas is a major priority in the United States.  To properly educate the leaders of tomorrow, we must move beyond the centuries-old, ingrained … Continue reading

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