搜索资源列表
fminlbfgs_version2
- 这是一个快速的拟牛顿法程序，非常实用，非常强大-FMINLBFGS is a Memory efficient optimizer for problems such as image registration with large amounts of unknowns, and cpu-expensive gradients. Supported: - Quasi Newton Broyden–Fletcher–Goldfarb–Shanno (BFGS). -
liblbfgs-1.7
- This library is a C port of the implementation of Limited-memory Broyden-Fletcher-Goldfarb-Shanno (L-BFGS) method written by Jorge Nocedal. The original FORTRAN source code is available at: This library is a C port of the implementation of Limited
L-BFGS
- 自己编的，实现l-bfgs解无约束优化问题-Own, and the realization of l-bfgs Unconstrained optimization problems
LBFGS-20020202.java
- L-BFGS用于内存紧张的系统中，可以用于求解大规模数据集的优化-Software for Large-scale Unconstrained Optimization L-BFGS is a limited-memory quasi-Newton code for large-scale unconstrained optimization.
SnOW
- This package provides a Maximum Entropy Modeling toolkit written in C++ with Python binding. It includes: Conditional Maximum Entropy Model L-BFGS Parameter Estimation GIS Parameter Estimation Gaussian Prior Smoothing C++ API
fminlbfgs_version2
- 可以实现大规模的bfgs功能，进行目标函数的最优化求解，即L-BFGS-Can achieve large scale bfgs function, the objective function is the most optimal solution, ie, L-BFGS
Lbfgsb.3.0.tar
- 无约束优化中非常有用的L-BFGS代码,在解决大规模优化问题中,有着良好的数值表现.-useful unconstrained optimization L-BFGS code, in the solution of large-scale optimization problems, has a good numerical performance.
L-BFGSPCODE
- 本程序是数值计算中FGS方法的改进型BFGS的代码，可以直接使用-This program is a modified BFGS method of numerical calculation FGS code can be used directly
L-BFGS源代码
- 这是一个L-BFGS的Matlab源代码
liblbfgs-1.9.tar
- 拟牛顿算法计算函数最小值，采用LBFGS算法，亲测可用。-a C port of the implementation of Limited-memory Broyden-Fletcher-Goldfarb-Shanno (L-BFGS) method written by Jorge Nocedal.
L-BFGS-CODE
- L-BFGS有限内存BFGS法,用于求解大规模无约束最优化问题-L-BFGS method for large scale unconstrained optimization
lbfgs
- L-BFGS算法比较适合在大规模的数值计算中，具备牛顿法收敛速度快的特点，但不需要牛顿法那样存储Hesse矩阵，因此节省了大量的空间以及计算资源。-Limited-memory BFGS (L-BFGS or LM-BFGS) is an optimization algorithm in the family of quasi-Newton methods that approximates the Broyden–Fletcher–Goldfarb–Shanno (BFGS) algorit
Deep-ADMM-Net-master
- Net is defined over a data flow graph, which is derived from the iterative pro- cedures in Alternating Direction Method of Multipliers (ADMM) algorithm for optimizing a CS-based MRI model. In the training phase, all parameters of the net, e.g., im
L-BFGS
- 有限记忆算法，用于处理大规模算法，算法原理为把不断迭代的牛顿矩阵分解并部分抵消达到减少运算量的目的(limit memory,for large-scale algorithms. The principle of the algorithm is to decompose and partially cancel the iterative Newton matrix in order to reduce the computational complexity.)