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This paper develops theoretical results regarding noisy 1-bit compressed sensing and sparse binomial regression.
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Regime Change: Sampling Rate vs. Bit-Depth in Compressive Sensing
Laska, J · 2011
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Introduction to the non-asymptotic analysis of random matrices
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Sobolev duals for random frames and sigma-delta quantization of compressed sensing measurements
Gunturk, C., Lammers, M., Powell, A., Saab, R., and Ylmaz, O
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Robust 1-bit compressive sensing via binary stable embeddings of sparse vectors
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Learning exponential families in high-dimensions: Strong convexity and sparsity
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Regime change: Bit-depth versus measurement-rate in compressive sensing
Laska, J., and Baraniuk, R
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Compressed Sensing
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