搜索资源列表
lbfgs
- 可以解决无约束的最优化问题，如求目标函数的极值等。
lbfgs.f90
- BFGS算法: 可以解决无约束的最优化问题，如求目标函数的极值等。
Lbfgs相关资料
- 对LBFGS及BFGS算法做了较为详细的说明
lbfgs
- 最大熵 等模型使用的 lbfgs 训练源代码。-Maximum entropy model, such as training to use the source code lbfgs.
lbfgs.cpp
- LBFGS ported to pure C. Exactly the same as the original Fotran implementation.
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
phase_div
- 基于盲解卷积的相位差算法，图像恢复，文件包里面有仿真和LBFGS优化算法-The phase difference based on blind deconvolution algorithm, vogel
BFGS-youhua
- 用于解决优化问题中的无约束优化,经过检测，能够成功运行。-To solve the problem of unconstrained optimization.
liblbfgs-1.8.tar
- lbfgs算法的库程序 快速有效采用C++编写 强烈推荐-lbfgs algorithms quickly and efficiently strongly recommended
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.
ofdm_lbfgs
- Main fuction is to reduce PAPR of OFDM by LBFGS scheme
lbfgs
- This submission contains an interface to a LBFGS-code for unconstrained minimization problems of the form min_{x} f(x) + c*|\tilde{x}|, where x are the parameters, f is a scalar valued real function, c is a positive scalar (default value=0), |.|
CRFPP-0.53
- 基于CRF++-0.53的改良版，修正了模型输入时多行空行导致的线程错误，优化了多线程操作，除LBFGS无法优化外，其余迭代操作全部多线程化，66MB模型在16线程服务器上运行，内存占用5.35GB，CPU利用率一般100 ，只有运行LBFGS时为7 。仅支持64位Windows操作系统，使用VC2008编译，不支持32位操作系统或Linux（Windows线程模型）。-Optimized CRF++-0.53. Fixed multi-empty line input bug. Optimiz
LBFGS
- 解二次函数的LBFGS算法,包括几个子程序，并且用了wolfe 线性搜索法-LBFGS algorithm for solving quadratic function
LBFGS
- 解二次函数的LBFGS方法,用了wolfe线性搜索，计算量较小,绝对可用。-Solving quadratic the function of LBFGS method with the wolfe linear search less computation absolutely available.
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.
LBFGS
- 用于最优化方法的LBFGS算法，可有效减少计算海森矩阵时的内存占用-The method for optimizing the LBFGS algorithm can effectively reduce the memory footprint when calculated Hessian matrix
LBFGS
- LBFGS Optimization algorithm in matlab
LBFGS
- lbfgs more fast and stable than matlab's fmincom(-> lbfgs)