Progressive Batching for Efficient Non-linear Least Squares

10/21/2020
by   Huu Le, et al.
0

Non-linear least squares solvers are used across a broad range of offline and real-time model fitting problems. Most improvements of the basic Gauss-Newton algorithm tackle convergence guarantees or leverage the sparsity of the underlying problem structure for computational speedup. With the success of deep learning methods leveraging large datasets, stochastic optimization methods received recently a lot of attention. Our work borrows ideas from both stochastic machine learning and statistics, and we present an approach for non-linear least-squares that guarantees convergence while at the same time significantly reduces the required amount of computation. Empirical results show that our proposed method achieves competitive convergence rates compared to traditional second-order approaches on common computer vision problems, such as image alignment and essential matrix estimation, with very large numbers of residuals.

READ FULL TEXT
POST COMMENT

Comments

There are no comments yet.

Authors

page 19

02/23/2017

Stochastic Newton and Quasi-Newton Methods for Large Linear Least-squares Problems

We describe stochastic Newton and stochastic quasi-Newton approaches to ...
06/23/2020

An efficient Averaged Stochastic Gauss-Newton algorithm for estimating parameters of non linear regressions models

Non linear regression models are a standard tool for modeling real pheno...
06/23/2020

An efficient Averaged Stochastic Gauss-Newtwon algorithm for estimating parameters of non linear regressions models

Non linear regression models are a standard tool for modeling real pheno...
09/03/2019

miniSAM: A Flexible Factor Graph Non-linear Least Squares Optimization Framework

Many problems in computer vision and robotics can be phrased as non-line...
11/02/2020

Asynchronous Parallel Stochastic Quasi-Newton Methods

Although first-order stochastic algorithms, such as stochastic gradient ...
05/03/2014

Supervised Descent Method for Solving Nonlinear Least Squares Problems in Computer Vision

Many computer vision problems (e.g., camera calibration, image alignment...
09/04/2018

Matrix Difference in Pose-Graph Optimization

Pose-Graph optimization is a crucial component of many modern SLAM syste...
This week in AI

Get the week's most popular data science and artificial intelligence research sent straight to your inbox every Saturday.