Scalable Incremental Nonconvex Optimization Approach for Phase Retrieval
نویسندگان
چکیده
منابع مشابه
Misspecified Nonconvex Statistical Optimization for Phase Retrieval
Existing nonconvex statistical optimization theory and methods crucially rely on the correct specification of the underlying “true” statistical models. To address this issue, we take a first step towards taming model misspecification by studying the high-dimensional sparse phase retrieval problem with misspecified link functions. In particular, we propose a simple variant of the thresholded Wir...
متن کاملA Nonconvex Approach for Phase Retrieval: Reshaped Wirtinger Flow and Incremental Algorithms
We study the problem of solving a quadratic system of equations, i.e., recovering a vector signal x ∈ R from its magnitude measurements yi = |〈ai,x〉|, i = 1, ...,m. We develop a gradient descent algorithm (referred to as RWF for reshaped Wirtinger flow) by minimizing the quadratic loss of the magnitude measurements. Comparing with Wirtinger flow (WF) (Candès et al., 2015), the loss function of ...
متن کاملFast Incremental Method for Nonconvex Optimization
We analyze a fast incremental aggregated gradient method for optimizing nonconvex problems of the form minx ∑ i fi(x). Specifically, we analyze the Saga algorithm within an Incremental First-order Oracle framework, and show that it converges to a stationary point provably faster than both gradient descent and stochastic gradient descent. We also discuss a Polyak’s special class of nonconvex pro...
متن کاملMedian-Truncated Nonconvex Approach for Phase Retrieval with Outliers∗†
This paper investigates the phase retrieval problem, which aims to recover a signal from the magnitudes of its linear measurements. We develop statistically and computationally efficient algorithms for the situation when the measurements are corrupted by sparse outliers that can take arbitrary values. We propose a novel approach to robustify the gradient descent algorithm by using the sample me...
متن کاملAn alternating optimization approach for phase retrieval
In this paper, we address the problem of phase retrieval to recover a signal from the magnitude of its Fourier transform. In many applications of phase retrieval, the signals encountered are naturally sparse. In this work, we consider the case where the signal is sparse under the assumption that few components are nonzero. We exploit further the sparse nature of the signals and propose a two st...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Journal of Scientific Computing
سال: 2021
ISSN: 0885-7474,1573-7691
DOI: 10.1007/s10915-021-01425-y