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8 - Principal component analysis in high dimensions
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5 - Metric entropy and its uses
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- 21 February 2019, pp 121-158
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Illustrations
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1 - Introduction
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9 - Decomposability and restricted strong convexity
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- 21 February 2019, pp 259-311
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15 - Minimax lower bounds
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References
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13 - Nonparametric least squares
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3 - Concentration of measure
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Author index
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6 - Random matrices and covariance estimation
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14 - Localization and uniform laws
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Contents
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4 - Uniform laws of large numbers
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12 - Reproducing kernel Hilbert spaces
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- 21 February 2019, pp 383-415
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10 - Matrix estimation with rank constraints
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- 21 February 2019, pp 312-346
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List of chapters
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Subject index
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2 - Basic tail and concentration bounds
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7 - Sparse linear models in high dimensions
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