Compressed Sensing with 1D Total Variation: Breaking Sample Complexity Barriers via Non-Uniform Recovery

Keyphrases

• Sample Complexity 100%
• Total Variation 100%
• Compressed Sensing 100%
• Uniform Recovery 100%
• Sqrt 66%
• Sampling Rate 66%
• Sparse Signal 66%
• Total Variation Regularization 66%
• Gradient Sparse 66%
• Large Classes 33%
• Undersampling 33%
• High Probability 33%
• Spatial Dimension 33%
• Rigorous Analysis 33%
• Typical Behavior 33%
• High-dimensional Problems 33%
• Robust Recovery 33%
• Gaussian Measurements 33%
• Jump Discontinuity 33%
• Piecewise Constant Functions 33%
• Gaussian Mean Width 33%
• Stable Recovery 33%
• Signal-dependent 33%
• Haar Wavelet Transform 33%
• Natural Signals 33%

Mathematics

• Nonuniform 100%
• Total Variation 100%
• Gaussian Distribution 66%
• Sampling Rate 66%
• Probability Theory 33%
• Upper Bound 33%
• Discretization 33%
• Jump Discontinuity 33%
• Constant Function 33%
• Haar Wavelet 33%
• Dimensional Problem 33%
• Main Result 33%
• Spatial Dimension 33%
• Wavelet Transforms 33%

Engineering

• Compressed Sensing 100%
• Total Variation 100%
• Gaussians 66%
• Sparse Signal 66%
• Sampling Rate 66%
• Spatial Dimension 33%
• Main Result 33%
• Dimensional Problem 33%
• Rigorous Analysis 33%
• Signal Vector 33%
• Discretization 33%