Large-scale distributed L-BFGS

نویسندگان
چکیده

برای دانلود رایگان متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Large-scale L-BFGS using MapReduce

L-BFGS has been applied as an effective parameter estimation method for various machine learning algorithms since 1980s. With an increasing demand to deal with massive instances and variables, it is important to scale up and parallelize L-BFGS effectively in a distributed system. In this paper, we study the problem of parallelizing the L-BFGS algorithm in large clusters of tens of thousands of ...

متن کامل

L-bfgs-b { Fortran Subroutines for Large-scale Bound Constrained Optimization

L BFGS B is a limited memory algorithm for solving large nonlinear optimization problems subject to simple bounds on the variables It is intended for problems in which information on the Hessian matrix is di cult to obtain or for large dense problems L BFGS B can also be used for unconstrained problems and in this case performs similarly to its predecessor algorithm L BFGS Harwell routine VA Th...

متن کامل

LM-CMA: An Alternative to L-BFGS for Large-Scale Black Box Optimization

Limited-memory BFGS (L-BFGS; Liu and Nocedal, 1989 ) is often considered to be the method of choice for continuous optimization when first- or second-order information is available. However, the use of L-BFGS can be complicated in a black box scenario where gradient information is not available and therefore should be numerically estimated. The accuracy of this estimation, obtained by finite di...

متن کامل

Large-scale Kalman Filtering Using the Limited Memory Bfgs Method

The standard formulations of the Kalman filter (KF) and extended Kalman filter (EKF) require the storage and multiplication of matrices of size n × n, where n is the size of the state space, and the inversion of matrices of size m × m, where m is the size of the observation space. Thus when both m and n are large, implementation issues arise. In this paper, we advocate the use of the limited me...

متن کامل

On the limited memory BFGS method for large scale optimization

We study the numerical performance of a limited memory quasi Newton method for large scale optimization which we call the L BFGS method We compare its performance with that of the method developed by Buckley and LeNir which combines cyles of BFGS steps and conjugate direction steps Our numerical tests indicate that the L BFGS method is faster than the method of Buckley and LeNir and is better a...

متن کامل

ذخیره 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 Big Data

سال: 2017

ISSN: 2196-1115

DOI: 10.1186/s40537-017-0084-5