本资源收录了机器学习课程用到的相关术语,涉及机器学习基础、机器学习理论、Applied Math、SVM、Ensemble、DNN、Regularization、Matrix Factorization、Optimization、CNN、 Auto Encoder、RNN、Representation、Network Embedding、GAN、Adversarial Learning、Online Learning、Reinforcement Learning、AutoML、Graphic Model、Topic Model、MCMC、Mean-Field、non-parametric models等。

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https://aminer.cn/ml_taxonomy

 

机器学习基础


英文 中文 相关学者 相关论文
Supervised Learning 监督学习 Michael I. Jordan   更多 Overview of Supervised Learning   更多
Unsupervised Learning 无监督学习

Andrew Y. Ng(吴恩达)   更多

Building high-level features using large scale unsupervised learning   更多
Semi-supervised Learning 半监督学习 

Zhihua Zhou(周志华)   更多

Semi-Supervised Learning Using Gaussian Fields and Harmonic Functions   更多
Reinforcement Learning 强化学习

Richard S. Sutton   更多

Reinforcement Learning: An Introduction  更多
Active Learning 主动学习

Jaime G. Carbonell   更多

Support vector machine active learning with applications to text classification   更多
Online Learning 在线学习

Steven HOI   更多

Adaptive Subgradient Methods for Online Learning and Stochastic Optimization   更多
Transfer Learning 迁移学习

Qiang Yang(杨强)   更多

Boosting for transfer learning   更多
Automated Machine Learning (AutoML) 自动机器学习

Michael Muller   更多

Efficient and Robust Automated Machine Learning   更多
Representation Learning 表示学习

Geoffrey E. Hinton   更多

InfoGAN: Interpretable Representation Learning by Information Maximizing Generative Adversarial Nets   更多

Minkowski distance 闵可夫斯基距离

Rudolf Mathar   更多

Fuzzy clustering with squared Minkowski distances   更多

Gradient Descent 梯度下降

Nathan Srebro   更多

Learning to rank using gradient descent   更多
Stochastic Gradient Descent 随机梯度下降

Pu Zhou(周朴)   更多

Large-Scale Machine Learning with Stochastic Gradient Descent   更多
Over-fitting 过拟合

Erin Kelly   更多

On Over-fitting in Model Selection and Subsequent Selection Bias in Performance Evaluation   更多

Regularization 正则化 

Stanley Osher   更多

Regularization and variable selection via the elastic net   更多
Cross Validation 交叉验证 

Sandrine Dudoit   更多

Estimating the Error Rate of a Prediction Rule: Improvement on Cross-Validation   更多
Perceptron 感知机

Shun-Ichi Amari     更多

 Discriminative training methods for hidden Markov models: theory and experiments with perceptron algorithms   更多

Logistic Regression 逻辑回归 David W. Hosmer   更多 Applied logistic regression   更多
Maximum Likelihood Estimation 最大似然估计 Mark J. Van Der Laan   更多 MAXIMUM LIKELIHOOD ESTIMATION AND INFERENCE ON COINTEGRATION - WITH APPLICATIONS TO THE DEMAND FOR MONEY    更多
Newton’s method 牛顿法

Liqun Qi(祁力群)   更多

Inexact Newton Methods   更多
K-Nearest Neighbor K近邻法

Cyrus Shahabi  更多

Fast k Nearest Neighbor Search using GPU   更多

Mahanalobis Distance 马氏距离

Shuran Song   更多

Implementation Hough Method and Mahanalobis Distance In Iris Biometric Identification System   更多

Decision Tree 决策树

Xizhao Wang(王熙照)   更多

Simplifying decision trees   更多
Naive Bayes Classifier 朴素贝叶斯分类器

Geoffrey I. Webb   更多

Scaling Up the Accuracy of Naive-Bayes Classifiers: A Decision-Tree Hybrid   更多