Comments (3)
jindongwang
commented on July 24, 2024
看附件，可以直接用
发件人： leshansanren<mailto:[email protected]>
发送时间： 2018-03-03 15:06:16
收件人： jindongwang/transferlearning<mailto:[email protected]>
抄送： Subscribed<mailto:[email protected]>
主题： [jindongwang/transferlearning] 关于GFK算法中d的确定 (#15)
王老师你好！我在应用GFK算法时，利用SDM方法确定d的个数，我的S是30x28的矩阵，T是30x28的矩阵，则S+T应该为60x28维的矩阵（不知道对不对？），再利用SDM求解两个domain与S+T的空间的夹角时，利用pca对三个数据集进行降维以后，不知道该怎么进行下一步求解sin（αd）和sin（βd）？我试过先求余弦值，再根据公式转换，但是求解数据长度不一致的余弦值应该怎么求？还有就是在求解夹角的时候是应该求pca以后的S和T与S+T的第1,2，…，d个向量的夹角，还是应该分别求d=1,2,3，…时的d维矩阵的夹角？
—
You are receiving this because you are subscribed to this thread.
Reply to this email directly, view it on GitHub<#15>, or mute the thread<https://github.com/notifications/unsubscribe-auth/AF33fsIc6IowuaxxTuFiDLHwlPS3pJz2ks5takDogaJpZM4Saz-O>.
from transferlearning.
leshansanren
commented on July 24, 2024
王老师，你是在国外吗？非常抱歉！这么晚还打扰您！您说的附件是？是MyGFK.m这个文件还是其他什么文件？我在使用您的MyGFK.m文件的时候的确可以直接应用，但还是无法直接确定d的取值，然而d的取值对我的识别结果是有影响的，我不能随意设置一个d值来进行识别。。。我是初学者，有很多问题都不太明白，希望您的答复能更详细一些，给您添麻烦了，再次感到万分抱歉！
from transferlearning.
leshansanren
commented on July 24, 2024
没关系，给您添麻烦了！再次感谢您的帮助，谢谢！
from transferlearning.
Related Issues (20)
- MMD距离 backward问题 HOT 3
- BDA代码中的数据集的问题 HOT 2
- 关于TransferNet中source_clf计算的疑问 HOT 1
- 关于复现 HOT 1
- 对比算法的复现缺少部分流程 HOT 1
- 程序显示没有loss_funcs模块 HOT 1
- Our new test-time adaptation algorithm for segmentation HOT 3
- 关于transferlearning/code /DeepDA的模型代码读取 HOT 2
- How to use DIFEX for single domain generalization? HOT 2
- code add HOT 2
- 有关于在使用DG中DANN方法中遇到的问题
- Office-31 webcam域上微调模型丢失 HOT 1
- 是否需要进行微调？ HOT 2
- 作者您好！请问AdaRNN的对比实验中，MMD-RNN和DANN-RNN是如何实现的，MMD-RNN的源域和目标域是如何定义的，AdaRNN相比这两个对比模型进步在哪里？ HOT 1
- Feature Request：添加ADDA的代码以及与其他方法的比较。 HOT 1
- 王老师您好，Domain Generalization for Activity Recognition via Adaptive Feature Fusion请问这篇论文的代码具体在哪个文件夹里？找了很久没找到 HOT 1
- Time series domain adaptation benchmark and datasets HOT 1
- DIVERSIFY: A General Framework for Time Series Out-of-distribution Detection and Generalization中的cross_dataset的文件 HOT 1
- BDA中A-distance问题
- 关于DANN中的域鉴别器的域分类准确率 HOT 2
Recommend Projects
-
React
A declarative, efficient, and flexible JavaScript library for building user interfaces.
-
Vue.js
🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.
-
Typescript
TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
-
TensorFlow
An Open Source Machine Learning Framework for Everyone
-
Django
The Web framework for perfectionists with deadlines.
-
Laravel
A PHP framework for web artisans
-
D3
Bring data to life with SVG, Canvas and HTML. 📊📈🎉
-
Recommend Topics
-
javascript
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
-
web
Some thing interesting about web. New door for the world.
-
server
A server is a program made to process requests and deliver data to clients.
-
Machine learning
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
-
Visualization
Some thing interesting about visualization, use data art
-
Game
Some thing interesting about game, make everyone happy.
Recommend Org
-
Facebook
We are working to build community through open source technology. NB: members must have two-factor auth.
-
Microsoft
Open source projects and samples from Microsoft.
-
Google
Google ❤️ Open Source for everyone.
-
Alibaba
Alibaba Open Source for everyone
-
D3
Data-Driven Documents codes.
-
Tencent
China tencent open source team.
from transferlearning.