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。

ICML 2012

Maximum Margin Output Coding

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

ICML 2011

Learning Discriminative Fisher Kernels

Learning Multi-View Neighborhood Preserving Projections

CVPR 2012

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

Group Action Induced Distances for Averaging and Clustering Linear Dynamical Systems with Applications
to the Analysis of Dynamic Visual Scenes

CVPR
2011

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)

ACM MM 2012

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

ICCV
2011

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

ECCV
2012

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

IJCAI 2011

Distance Metric Learning Under Covariate Shift

Learning a Distance Metric by Empirical Loss Minimization

AAAI
2011

Efficiently Learning a Distance Metric for Large Margin Nearest Neighbor Classification

NIPS
2011

Learning a Distance Metric from a Network

Learning a Tree of Metrics with Disjoint Visual Features

Metric Learning with Multiple Kernels

KDD 2012

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

  1. 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 ...

  2. 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 ...

  3. 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 ...

  4. 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. ...

  5. 【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 ...

  6. 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 ...

  7. 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 ...

  8. 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 ...

  9. 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

  1. 使用Autofac 依赖注入及 swagger 之startup配置

    言语有限,代码如下: public IServiceProvider ConfigureServices(IServiceCollection services) { services .AddCor ...

  2. sql 区分大小写查询

    sql 区分大小写查询 select * FROM [Users] where userName collate Chinese_PRC_CS_AS='ADMIN'

  3. BZOJ 4032 Luogu P4112 [HEOI2015]最短不公共子串 (DP、后缀自动机)

    这其实是道水题... 题目链接: (bzoj)https://www.lydsy.com/JudgeOnline/problem.php?id=4032 (luogu)https://www.luog ...

  4. 常用Git命令大全思维导图

    开发中代码管理少不了使用Git,对于初学者来说Git命令的学习是一个难过的坎,为了帮助大家记忆并快速掌握Git的基本使用,我把常用的Git命令整理成思维导图,分享给大家. 高清大图在线预览 http: ...

  5. C - Reading comprehension 二分法 求等比数列前N项和

    Read the program below carefully then answer the question. #pragma comment(linker, "/STACK:1024 ...

  6. Git 项目上传至github入门实战并解决常见错误

    1.Git GUI 首先,在push到github的项目必须先建立版本(即creat  repository的名字一样),一般是先pull下来,再push(为了防止有其他人提交了代码,而你却不知道,造 ...

  7. gap lock/next-key lock浅析 Basic-Paxos协议日志同步应用

    http://www.cnblogs.com/renolei/p/4673842.html 当InnoDB在判断行锁是否冲突的时候, 除了最基本的IS/IX/S/X锁的冲突判断意外, InnoDB还将 ...

  8. MVC.Net:压缩/保存图片缩略图

    通常用户上传的图片需要压缩或者生成缩略图.用System.Web.Helpers.WebImage的Resize方法可以很方便的实现这一功能.示例代码如下: /// <summary> / ...

  9. 在imageView依次加入7个手势, 1.点击哪个button,往imageView上加入哪个手势.(保证视图上仅仅有一个手势). 2.轻拍:点击视图切换美女图片.(imageView上首先展示的美女

    // // ControlView.h // HomeworkGestureRecognizer // // Created by lanouhn on 14-8-27. // Copyright ( ...

  10. IntelliJ IDEA 14注冊码

    User:xring Key:21423-V4P36-U7W8K-8CYUK-93HXA-MKGZ5 User:arix Key:52998-LJT74-J7YEX-UPVT3-Q5GUF-5G4B5 ...