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Wavefield reconstruction inversion (WRI) extends the search space of Full Waveform Inversion (FWI) by allowing for wave equation errors during wavefield reconstruction to match the data from the first iteration. Then, the wavespeeds are…

Optimization and Control · Mathematics 2020-05-18 Hossein S. Aghamiry , Ali Gholami , Stéphane Operto

Full-waveform inversion (FWI) with extended sources first computes wavefields with data-driven source extensions, such that the simulated data in inaccurate velocity models match the observed counterpart well enough to prevent cycle…

Geophysics · Physics 2023-03-03 Gaoshan Guo , Stephane Operto , Ali Gholami , Hossein S. Aghamiry

In this paper, we propose an inexact Augmented Lagrangian Method (ALM) for the optimization of convex and nonsmooth objective functions subject to linear equality constraints and box constraints where errors are due to fixed-point data. To…

Optimization and Control · Mathematics 2019-07-23 Yan Zhang , Michael M. Zavlanos

Most recently, He and Yuan [arXiv:2108.08554, 2021] have proposed a balanced augmented Lagrangian method (ALM) for the canonical convex programming problem with linear constraints, which advances the original ALM by balancing its…

Optimization and Control · Mathematics 2021-12-30 Shengjie Xu

Full Waveform Inversion (FWI) is a successful and well-established inverse method for reconstructing material models from measured wave signals. In the field of seismic exploration, FWI has proven particularly successful in the…

Computational Engineering, Finance, and Science · Computer Science 2023-12-05 Tim Bürchner , Philipp Kopp , Stefan Kollmannsberger , Ernst Rank

We present Lift and Relax for Waveform Inversion (LRWI), an approach that mitigates the local minima issue in seismic full waveform inversion (FWI) via a combination of two convexification techniques. The first technique (Lift) extends the…

Optimization and Control · Mathematics 2021-09-08 Zhilong Fang , Laurent Demanet

Lagrangian methods are widely used algorithms for constrained optimization problems, but their learning dynamics exhibit oscillations and overshoot which, when applied to safe reinforcement learning, leads to constraint-violating behavior…

Optimization and Control · Mathematics 2020-07-09 Adam Stooke , Joshua Achiam , Pieter Abbeel

In this paper, we consider large-scale linearly constrained composite convex optimization problem, whose objective is a sum of a smooth function and a possibly nonsmooth function. We propose a scalable \textbf{F}rank-\textbf{W}olfe based…

Optimization and Control · Mathematics 2015-10-13 Ya-Feng Liu , Xiangfeng Wang , Xin Liu , Shiqian Ma

The Augmented Lagrangian Method (ALM) is an iterative method for the solution of equality-constrained non-linear programming problems. In contrast to the quadratic penalty method, the ALM can satisfy equality constraints in an exact way.…

Numerical Analysis · Mathematics 2018-04-24 Martin Neuenhofen

We present a robust immersed boundary (IB) method for high density ratio multiphase flows that is capable of modeling complex wave-structure interaction (WSI) problems arising in marine and coastal engineering applications. The IB/WSI…

Fluid Dynamics · Physics 2019-09-04 Nishant Nangia , Neelesh A. Patankar , Amneet Pal Singh Bhalla

A new formulation of the immersed boundary method, which facilitates accurate simulation of incompressible isothermal and natural convection flows around immersed bodies and which may be applied for accurate linear stability analysis of the…

Fluid Dynamics · Physics 2015-12-17 Yuri Feldman , Yosef Gulberg

This paper proposes a computationally efficient algorithm to address the Full-Waveform Inversion (FWI) problem with a Total Variation (TV) constraint, designed to accurately reconstruct subsurface properties from seismic data. FWI, as an…

Signal Processing · Electrical Eng. & Systems 2025-01-15 Yudai Inada , Shingo Takemoto , Shunsuke Ono

In this paper, we investigate sequential power allocation over fast varying channels for mission-critical applications, aiming to minimize the expected sum power while guaranteeing the transmission success probability. In particular, a…

Information Theory · Computer Science 2023-06-09 Chongtao Guo , Zhengchao Li , Le Liang , Geoffrey Ye Li

Physics and equality constrained artificial neural networks (PECANN) are grounded in methods of constrained optimization to properly constrain the solution of partial differential equations (PDEs) with their boundary and initial conditions…

Machine Learning · Computer Science 2023-07-18 Shamsulhaq Basir , Inanc Senocak

We propose a formulation of full-wavefield inversion (FWI) as a constrained optimization problem, and describe a computationally efficient technique for solving constrained full-wavefield inversion (CFWI). The technique is based on using a…

Geophysics · Physics 2014-10-28 Musa Maharramov , Biondo Biondi

We propose and test a method to reduce the dimensionality of Full Waveform Inversion (FWI) inputs as computational cost mitigation approach. Given modern seismic acquisition systems, the data (as input for FWI) required for an…

Machine Learning · Computer Science 2026-01-06 Maayan Gelboim , Amir Adler , Mauricio Araya-Polo

We present a numerical method for the minimization of objectives that are augmented with large quadratic penalties of overdetermined inconsistent equality constraints. Such objectives arise from quadratic integral penalty methods for the…

Optimization and Control · Mathematics 2020-09-15 Martin P. Neuenhofen , Eric C. Kerrigan

Extended formulation of Full Waveform Inversion (FWI), called Wavefield Reconstruction Inversion (WRI), offers potential benefits of decreasing the nonlinearity of the inverse problem by replacing the explicit inverse of the ill-conditioned…

Optimization and Control · Mathematics 2020-05-18 Hossein S. Aghamiry , Ali Gholami , Stéphane Operto

We introduce a twice differentiable augmented Lagrangian for nonlinear optimization with general inequality constraints and show that a strict local minimizer of the original problem is an approximate strict local solution of the augmented…

Optimization and Control · Mathematics 2021-06-30 Xin-Wei Liu , Yu-Hong Dai , Ya-Kui Huang , Jie Sun

We consider the augmented Lagrangian method (ALM) as a solver for the fused lasso signal approximator (FLSA) problem. The ALM is a dual method in which squares of the constraint functions are added as penalties to the Lagrangian. In order…

Computation · Statistics 2010-05-28 Heng Lian