4.6 Article

Just Least Squares: Binary Compressive Sampling with Low Generative Intrinsic Dimension

相关参考文献

注意:仅列出部分参考文献,下载原文获取全部文献信息。
Article Mathematics, Applied

A Provably Convergent Scheme for Compressive Sensing Under Random Generative Priors

Wen Huang et al.

Summary: Deep generative modeling offers low-dimensional parameterizations of image or signal manifolds for recovery algorithms, with linear sample complexity scaling in input dimensionality. An algorithm based on gradient descent is presented under the assumption of a sufficiently expansive neural network generative model with Gaussian weights, providing recovery guarantees for compressive sensing under generative priors.

JOURNAL OF FOURIER ANALYSIS AND APPLICATIONS (2021)

Article Mathematics, Applied

Memory Capacity of Neural Networks with Threshold and Rectified Linear Unit Activations

Roman Vershynin

SIAM JOURNAL ON MATHEMATICS OF DATA SCIENCE (2020)

Article Computer Science, Artificial Intelligence

Nonlinear approximation via compositions

Zuowei Shen et al.

NEURAL NETWORKS (2019)

Article Computer Science, Artificial Intelligence

Pinball loss minimization for one-bit compressive sensing: Convex models and algorithms

Xiaolin Huang et al.

NEUROCOMPUTING (2018)

Article Mathematics, Applied

ROBUST DECODING FROM 1-BIT COMPRESSIVE SAMPLING WITH ORDINARY AND REGULARIZED LEAST SQUARES

Jian Huang et al.

SIAM JOURNAL ON SCIENTIFIC COMPUTING (2018)

Article Mathematics, Applied

Noisy 1-bit compressive sensing: models and algorithms

Dao-Qing Dai et al.

APPLIED AND COMPUTATIONAL HARMONIC ANALYSIS (2016)

Article Computer Science, Information Systems

The Generalized Lasso With Non-Linear Observations

Yaniv Plan et al.

IEEE TRANSACTIONS ON INFORMATION THEORY (2016)

Article Mathematics, Applied

One-Bit Compressed Sensing by Greedy Algorithms

Wenhui Liu et al.

NUMERICAL MATHEMATICS-THEORY METHODS AND APPLICATIONS (2016)

Article Mathematics, Applied

One-Bit Compressed Sensing by Linear Programming

Yaniv Plan et al.

COMMUNICATIONS ON PURE AND APPLIED MATHEMATICS (2013)

Article Computer Science, Information Systems

Robust 1-Bit Compressive Sensing via Binary Stable Embeddings of Sparse Vectors

Laurent Jacques et al.

IEEE TRANSACTIONS ON INFORMATION THEORY (2013)

Article Computer Science, Information Systems

Robust 1-bit Compressed Sensing and Sparse Logistic Regression: A Convex Programming Approach

Yaniv Plan et al.

IEEE TRANSACTIONS ON INFORMATION THEORY (2013)

Article Engineering, Electrical & Electronic

Regime Change: Bit-Depth Versus Measurement-Rate in Compressive Sensing

Jason N. Laska et al.

IEEE TRANSACTIONS ON SIGNAL PROCESSING (2012)

Article Engineering, Electrical & Electronic

Robust 1-bit Compressive Sensing Using Adaptive Outlier Pursuit

Ming Yan et al.

IEEE TRANSACTIONS ON SIGNAL PROCESSING (2012)

Article Engineering, Electrical & Electronic

Trust, But Verify: Fast and Accurate Signal Recovery From 1-Bit Compressive Measurements

Jason N. Laska et al.

IEEE TRANSACTIONS ON SIGNAL PROCESSING (2011)

Article Engineering, Electrical & Electronic

Compressed Sensing With Quantized Measurements

Argyrios Zymnis et al.

IEEE SIGNAL PROCESSING LETTERS (2010)

Article Computer Science, Information Systems

Compressed sensing

DL Donoho

IEEE TRANSACTIONS ON INFORMATION THEORY (2006)

Article Computer Science, Information Systems

Robust uncertainty principles:: Exact signal reconstruction from highly incomplete frequency information

EJ Candès et al.

IEEE TRANSACTIONS ON INFORMATION THEORY (2006)