Metric Learning度量学习:**矩阵学习和图学习
DML学习原文链接:http://blog.csdn.net/lzt1983/article/details/7884553
一篇metric learning(DML)的综述文章,对DML的意义、方法论和经典论文做一个介绍,同时对我的研究经历和思考做一个总结。可惜一直没有把握自己能够写好,因此拖到现在。
先列举一些DML的参考资源,以后有时间再详细谈谈。
1. Wikipedia
2. CMU的Liu Yang总结的关于DML的综述页面。对DML的经典算法进行了分类总结,其中她总结的论文非常有价值,也是我的入门读物。
3. ECCV 2010的turorial。
4. Weinberger的页面,上面有LMNN(Distance Metric Learning for Large Margin Nearest Neighbor Classification)的论文、sclides和代码。
5. ITML(Information Throretic Metric Learning)。ITML是DML的经典算法,获得了ICML 2007的best paper award。sclides。
顶级会议上矩阵学习的paper清单:http://blog.csdn.net/lzt1983/article/details/7831524
近2年顶级会议上度量学习相关的论文,数量之多,颇受震动。这其中怕是不乏灌水炒作新概念的文章,看来DML大有前几年sparse coding的势头啊。
Information-theoretic Semi-supervised Metric Learning via Entropy Regularization
A Hybrid Algorithm for Convex Semidefinite Optimization
Information-Theoretical Learning of Discriminative Clusters for Unsupervised Domain Adaptation
Similarity Learning for Provably Accurate Sparse Linear Classification
Learning Discriminative Fisher Kernels
Learning Multi-View Neighborhood Preserving Projections
Order Determination and Sparsity-Regularized Metric Learning for Adaptive Visual Tracking
Non-sparse Linear Representations for Visual Tracking with Online Reservoir Metric Learning
Unsupervised Metric Fusion by Cross Diffusion
Learning Hierarchical Similarity Metrics
Large Scale Metric Learning from Equivalence Constraints
Neighborhood Repulsed Metric Learning for Kinship Verification
Learning Robust and Discriminative Multi-Instance Distance for Cost Effective Video Classification
PCCA: a new approach for distance learning from sparse pairwise constraints
A Scalable Dual Approach to Semidefinite Metric Learning
AdaBoost
on Low-Rank PSD Matrices for Metric Learning with Applications in Computer Aided Diagnosis
Adaptive Metric Differential Tracking (HUST)
Tracking Low Resolution Objects by Metric Preservation (HUST)
Optimal Semi-Supervised Metric Learning for Image Retrieval
Low Rank Metric Learning for Social Image Retrieval
Activity-Based Person Identification Using Sparse Coding and Discriminative Metric Learning
Deep Nonlinear Metric Learning with Independent Subspace Analysis for Face Verification
ACM MM 2011
Biased Metric Learning for Person-Independent Head Pose Estimation
Learning Mixtures of Sparse Distance Metrics for Classification and Dimensionality Reduction
Unsupervised Metric Learning for Face Identification in TV Video
Random Ensemble Metrics for Object Recognition
Learning Nonlinear Distance Functions using Neural Network for Regression with Application to Robust Human Age Estimation
Learning parameterized histogram kernels on the simplex manifold for image and action classification
Metric Learning for Large Scale Image Classification: Generalizing to New Classes at Near-Zero Cost
Dual-force Metric Learning for Robust Distractor Resistant Tracker
Learning to Match Appearances by Correlations in a Covariance Metric Space
Image Annotation Using Metric Learning in Semantic Neighbourhoods
Measuring Image Distances via Embedding in a Semantic Manifold
Supervised Earth Mover’s Distance Learning and Its Computer Vision Applications
Learning Class-to-Image Distance via Large Margin and L1-norm Regularization
Labeling Images by Integrating Sparse Multiple Distance Learning and Semantic Context Modeling
Distance Metric Learning Under Covariate Shift
Learning a Distance Metric by Empirical Loss Minimization
Efficiently Learning a Distance Metric for Large Margin Nearest Neighbor Classification
Learning a Distance Metric from a Network
Learning a Tree of Metrics with Disjoint Visual Features
Metric Learning with Multiple Kernels
Random Forests for Metric Learning with Implicit Pairwise Position Dependence
WSDM 2011
Mining Social Images with Distance Metric Learning for Automated
Image Tagging
Metric Learning度量学习:**矩阵学习和图学习的更多相关文章
- 关于图计算&图学习的基础知识概览:前置知识点学习(Paddle Graph Learning (PGL))
关于图计算&图学习的基础知识概览:前置知识点学习(Paddle Graph Learning (PGL)) 欢迎fork本项目原始链接:关于图计算&图学习的基础知识概览:前置知识点学习 ...
- Paddle Graph Learning (PGL)图学习之图游走类模型[系列四]
Paddle Graph Learning (PGL)图学习之图游走类模型[系列四] 更多详情参考:Paddle Graph Learning 图学习之图游走类模型[系列四] https://aist ...
- Reinforcement Learning,微信公众号:DRL学习
欢迎大家关注微信公众号:DRL学习,我们一起来学习强化学习和深度强化学习的算法及现状应用问题. 强化学习简单说就是学习如何最大化未来奖励的预期总和,以及agent学会在环境中做出的行动序列,其中随机状 ...
- 图学习【参考资料2】-知识补充与node2vec代码注解
本项目参考: https://aistudio.baidu.com/aistudio/projectdetail/5012408?contributionType=1 *一.正题篇:DeepWalk. ...
- 【转载】跟着9张思维导图学习JavaScript
原文:跟着9张思维导图学习JavaScript 学习的道路就是要不断的总结归纳,好记性不如烂笔头,so,下面将 po 出我收集的 9 张 JavaScript相关的思维导图(非原创). 思维导图小ti ...
- Comprehensive learning path – Data Science in Python深入学习路径-使用python数据中学习
http://blog.csdn.net/pipisorry/article/details/44245575 关于怎么学习python,并将python用于数据科学.数据分析.机器学习中的一篇非常好 ...
- 用Spark学习矩阵分解推荐算法
在矩阵分解在协同过滤推荐算法中的应用中,我们对矩阵分解在推荐算法中的应用原理做了总结,这里我们就从实践的角度来用Spark学习矩阵分解推荐算法. 1. Spark推荐算法概述 在Spark MLlib ...
- Learning ROS for Robotics Programming Second Edition学习笔记(六) indigo xtion pro live
中文译著已经出版,详情请参考:http://blog.csdn.net/ZhangRelay/article/category/6506865 Learning ROS for Robotics Pr ...
- Learning ROS for Robotics Programming Second Edition学习笔记(五) indigo computer vision
中文译著已经出版,详情请参考:http://blog.csdn.net/ZhangRelay/article/category/6506865 Learning ROS for Robotics Pr ...
随机推荐
- Linq表达式写法
Linq表达式,实现按照某个字段排序的简单写法. 做项目的时候遇到的一个简单问题,于是记下来. 列举一个例子: <T> model=new <T>(); 加入model中有要根 ...
- 强悍的 ubuntu —— 命令行访问网页
所谓以命令行的方式访问网页,即是在终端下以文本的形式访问网站,这里推荐一个工具:w3m, $ sudo apt-get install w3m $ w3m www.baidu.com
- 解析特殊格式的xml到map
由于项目特殊,需要解析的xml文档样式特别,所以自己写了一个解析特殊xml的方法 先提供xml样式 <?xml version="1.0" encoding="UT ...
- git 拉取远程分支 --本地分支不存在
git checkout -b 本地分支名 origin/远程分支名
- 嵌入式linux和嵌入式android系统有什么区别和联系?
转自:http://bbs.eeworld.com.cn/thread-430437-1-1.html 这个问题很多人问,尤其是初入嵌入式的菜鸟.其实大家都认为android是java,已经不是lin ...
- php生成随机password的几种方法
文章来源:PHP开发学习门户 地址:http://www.phpthinking.com/archives/523 使用PHP开发应用程序,尤其是站点程序.经常须要生成随机password,如用户注冊 ...
- CSS制作响应式正方形及其应用
CSS制作响应式正方形?什么鬼?干嘛用的?干嘛用的没人有每人的需求,本人也正好是由于公司正在做的业务须要,想做个照片展示的功能(当然得符合响应式了).而这个照片展示必须符合下面几点功能:1.用三张图片 ...
- iOS 运行时添加属性和方法
第一种:runtime.h里的方法 BOOL class_addProperty(Class cls, const char *name, const objc_property_attribute_ ...
- luogu1005 矩阵取数游戏
题目大意 一个矩阵,每次从每一行的行首或行尾取一个数,每一行的价值为 取的数*2^当前取数的次数,每一次的价值为每一行的价值的和.求得到的价值的最大值. 思路 #include <cstdio& ...
- React-Router 中文简明教程(上)
概述 说起 前端路由,如果你用过前端 MV* 框架构建 SPA 应用(单页面应用),对此一定不陌生. 传统开发中的 路由,是由服务端根据不同的用户请求地址 URL,返回不同内容的页面,而前端路由则将这 ...