文件名称:lib-mkl
下载
别用迅雷、360浏览器下载。
如迅雷强制弹出，可右键点击选“另存为”。
失败请重下，重下不扣分。
如迅雷强制弹出，可右键点击选“另存为”。
失败请重下，重下不扣分。
介绍说明－－下载内容均来自于网络，请自行研究使用
Multiple kernel learning is a model to merge multiple kernels by linear combination. Mostly solving the models are slow due to explicit computation of kernels.
Here, we propose to approximate kernel map function explicitly in finite dimensional space. Then, we use dual coordinate descent to solve the SVM. By storing the solutions in primal, we do not have to compute the kernel explicitly. A group lasso regularization on kernel weights is solved with SVM alternatingly.
This is a side-project in my research projects with Dr. Yi-Ren Yeh and Dr. Frank Wang in Academia Sinica.
Here, we propose to approximate kernel map function explicitly in finite dimensional space. Then, we use dual coordinate descent to solve the SVM. By storing the solutions in primal, we do not have to compute the kernel explicitly. A group lasso regularization on kernel weights is solved with SVM alternatingly.
This is a side-project in my research projects with Dr. Yi-Ren Yeh and Dr. Frank Wang in Academia Sinica.
(系统自动生成,下载前可以参看下载内容)
下载文件列表
lib-mkl
.......\libsvmread.c
.......\libsvmread.mexw64
.......\libsvmwrite.c
.......\libsvmwrite.mexw64
.......\linear.obj
.......\linear_model_matlab.c
.......\linear_model_matlab.h
.......\linear_model_matlab.obj
.......\make.m
.......\Makefile
.......\map
.......\...\libvl.so
.......\...\logistic.m
.......\...\poly2dense.m
.......\...\vl_homkermap.mexa64
.......\predict.c
.......\predict.mexw64
.......\predict_mkl.m
.......\README
.......\result.html
.......\run.m
.......\run_mkl.m
.......\startup.m
.......\train.c
.......\train.mexw64
.......\train_feature_select.m
.......\train_mkl.m
.......\tron.obj