機器學習相關英文術語
阿新 • • 發佈：2019-02-09
機器學習相關術語（按首字母排序）
| 縮寫 | 英語 | 漢語 |
|---|---|---|
| A | ||
| Activation Function | 啟用函式 | |
| Adversarial Networks | 對抗網路 | |
| Affine Layer | 仿射層 | |
| agent | 代理/智慧體 | |
| algorithm | 演算法 | |
| alpha-beta pruning | α-β剪枝 | |
| anomaly detection | 異常檢測 | |
| approximation | 近似 | |
| AGI | Artificial General Intelligence | 通用人工智慧 |
| AI | Artificial Intelligence | 人工智慧 |
| association analysis | 關聯分析 | |
| attention mechanism | 注意機制 | |
| autoencoder | 自編碼器 | |
| ASR | automatic speech recognition | 自動語音識別 |
| automatic summarization | 自動摘要 | |
| average gradient | 平均梯度 | |
| Average-Pooling | 平均池化 | |
| B | ||
| BP | backpropagation | 反向傳播 |
| BPTT | Backpropagation Through Time | 通過時間的反向傳播 |
| BN | Batch Normalization | 分批標準化 |
| Bayesian network | 貝葉斯網路 | |
| Bias-Variance Dilemma | 偏差/方差困境 | |
| Bi-LSTM | Bi-directional Long-Short Term Memory | 雙向長短期記憶 |
| bias | 偏置/偏差 | |
| big data | 大資料 | |
| Boltzmann machine | 玻爾茲曼機 | |
| C | ||
| CPU | Central Processing Unit | 中央處理器 |
| chunk | 詞塊 | |
| clustering | 聚類 | |
| cluster analysis | 聚類分析 | |
| co-adapting | 共適應 | |
| co-occurrence | 共現 | |
| Computation Cost | 計算成本 | |
| Computational Linguistics | 計算語言學 | |
| computer vision | 計算機視覺 | |
| concept drift | 概念漂移 | |
| CRF | conditional random field | 條件隨機域/場 |
| convergence | 收斂 | |
| CA | conversational agent | 會話代理 |
| convexity | 凸性 | |
| CNN | convolutional neural network | 卷積神經網路 |
| Cost Function | 成本函式 | |
| cross entropy | 交叉熵 | |
| D | ||
| Decision Boundary | 決策邊界 | |
| Decision Trees | 決策樹 | |
| DBN | Deep Belief Network | 深度信念網路 |
| DCGAN | Deep Convolutional Generative Adversarial Network | 深度卷積生成對抗網路 |
| DL | deep learning | 深度學習 |
| DNN | deep neural network | 深度神經網路 |
| Deep Q-Learning | 深度Q學習 | |
| DQN | Deep Q-Network | 深度Q網路 |
| DNC | differentiable neural computer | 可微分神經計算機 |
| dimensionality reduction algorithm | 降維演算法 | |
| discriminative model | 判別模型 | |
| discriminator | 判別器 | |
| divergence | 散度 | |
| domain adaption | 領域自適應 | |
| Dropout | ||
| Dynamic Fusion | 動態融合 | |
| E | ||
| Embedding | 嵌入 | |
| emotional analysis | 情緒分析 | |
| End-to-End | 端到端 | |
| EM | Expectation-Maximization | 期望最大化 |
| Exploding Gradient Problem | 梯度爆炸問題 | |
| ELM | Extreme Learning Machine | 超限學習機 |
| F | ||
| FAIR | Facebook Artificial Intelligence Research | Facebook人工智慧研究所 |
| factorization | 因子分解 | |
| feature engineering | 特徵工程 | |
| Featured Learning | 特徵學習 | |
| Feedforward Neural Networks | 前饋神經網路 | |
| G | ||
| game theory | 博弈論 | |
| GMM | Gaussian Mixture Model | 高斯混合模型 |
| GA | Genetic Algorithm | 遺傳演算法 |
| Generalization | 泛化 | |
| GAN | Generative Adversarial Networks | 生成對抗網路 |
| Generative Model | 生成模型 | |
| Generator | 生成器 | |
| Global Optimization | 全域性優化 | |
| GNMT | Google Neural Machine Translation | 谷歌神經機器翻譯 |
| Gradient Descent | 梯度下降 | |
| graph theory | 圖論 | |
| GPU | graphics processing unit | 圖形處理單元/圖形處理器 |
| H | ||
| HDM | hidden dynamic model | 隱動態模型 |
| hidden layer | 隱藏層 | |
| HMM | Hidden Markov Model | 隱馬爾可夫模型 |
| hybrid computing | 混合計算 | |
| hyperparameter | 超引數 | |
| I | ||
| ICA | Independent Component Analysis | 獨立成分分析 |
| input | 輸入 | |
| ICML | International Conference for Machine Learning | 國際機器學習大會 |
| language phenomena | 語言現象 | |
| latent dirichlet allocation | 隱含狄利克雷分佈 | |
| J | ||
| JSD | Jensen-Shannon Divergence | JS距離 |
| K | ||
| K-Means Clustering | K-均值聚類 | |
| K-NN | K-Nearest Neighbours Algorithm | K-最近鄰演算法 |
| Knowledge Representation | 知識表徵 | |
| KB | knowledge base | 知識庫 |
| L | ||
| Latent Dirichlet Allocation | 隱狄利克雷分佈 | |
| LSA | latent semantic analysis | 潛在語義分析 |
| learner | 學習器 | |
| Linear Regression | 線性迴歸 | |
| log likelihood | 對數似然 | |
| Logistic Regression | Logistic迴歸 | |
| LSTM | Long-Short Term Memory | 長短期記憶 |
| loss | 損失 | |
| M | ||
| MT | machine translation | 機器翻譯 |
| Max-Pooling | 最大池化 | |
| Maximum Likelihood | 最大似然 | |
| minimax game | 最小最大博弈 | |
| Momentum | 動量 | |
| MLP | Multilayer Perceptron | 多層感知器 |
| multi-document summarization | 多文件摘要 | |
| MLP | multi layered perceptron | 多層感知器 |
| multimodal learning | 多模態學習 | |
| multiple linear regression | 多元線性迴歸 | |
| N | ||
| Naive Bayes Classifier | 樸素貝葉斯分類器 | |
| named entity recognition | 命名實體識別 | |
| Nash equilibrium | 納什均衡 | |
| NLG | natural language generation | 自然語言生成 |
| NLP | natural language processing | 自然語言處理 |
| NLL | Negative Log Likelihood | 負對數似然 |
| NMT | Neural Machine Translation | 神經機器翻譯 |
| NTM | Neural Turing Machine | 神經圖靈機 |
| NCE | noise-contrastive estimation | 噪音對比估計 |
| non-convex optimization | 非凸優化 | |
| non-negative matrix factorization | 非負矩陣分解 | |
| Non-Saturating Game | 非飽和博弈 | |
| O | ||
| objective function | 目標函式 | |
| Off-Policy | 離策略 | |
| On-Policy | 在策略 | |
| one shot learning | 一次性學習 | |
| output | 輸出 | |
| P | ||
| Parameter | 引數 | |
| parse tree | 解析樹 | |
| part-of-speech tagging | 詞性標註 | |
| PSO | Particle Swarm Optimization | 粒子群優化演算法 |
| perceptron | 感知器 | |
| polarity detection | 極性檢測 | |
| pooling | 池化 | |
| PPGN | Plug and Play Generative Network | 即插即用生成網路 |
| PCA | principal component analysis | 主成分分析 |
| Probability Graphical Model | 概率圖模型 | |
| Q | ||
| QNN | Quantized Neural Network | 量子化神經網路 |
| quantum computer | 量子計算機 | |
| Quantum Computing | 量子計算 | |
| R | ||
| RBF | Radial Basis Function | 徑向基函式 |
| Random Forest Algorithm | 隨機森林演算法 | |
| ReLU | Rectified Linear Unit | 線性修正單元/線性修正函式 |
| RNN | Recurrent Neural Network | 迴圈神經網路 |
| recursive neural network | 遞迴神經網路 | |
| RL | reinforcement learning | 強化學習 |
| representation | 表徵 | |
| representation learning | 表徵學習 | |
| Residual Mapping | 殘差對映 | |
| Residual Network | 殘差網路 | |
| RBM | Restricted Boltzmann Machine | 受限玻爾茲曼機 |
| Robot | 機器人 | |
| Robustness | 穩健性 | |
| RE | Rule Engine | 規則引擎 |
| S | ||
| saddle point | 鞍點 | |
| Self-Driving | 自動駕駛 | |
| SOM | self organised map | 自組織對映 |
| Semi-Supervised Learning | 半監督學習 | |
| sentiment analysis | 情感分析 | |
| SLAM | simultaneous localization and mapping | 同步定位與地圖構建 |
| SVD | Singular Value Decomposition | 奇異值分解 |
| Spectral Clustering | 譜聚類 | |
| Speech Recognition | 語音識別 | |
| SGD | stochastic gradient descent | 隨機梯度下降 |
| supervised learning | 監督學習 | |
| SVM | Support Vector Machine | 支援向量機 |
| synset | 同義詞集 | |
| T | ||
| t-SNE | T-Distribution Stochastic Neighbour Embedding | T-分佈隨機近鄰嵌入 |
| tensor | 張量 | |
| TPU | Tensor Processing Units | 張量處理單元 |
| the least square method | 最小二乘法 | |
| Threshold | 闕值 | |
| Time Step | 時間步驟 | |
| tokenization | 標記化 | |
| treebank | 樹庫 | |
| transfer learning | 遷移學習 | |
| Turing Machine | 圖靈機 | |
| U | ||
| unsupervised learning | 無監督學習 | |
| V | ||
| Vanishing Gradient Problem | 梯度消失問題 | |
| VC Theory | Vapnik–Chervonenkis theory | 萬普尼克-澤範蘭傑斯理論 |
| von Neumann architecture | 馮·諾伊曼架構/結構 | |
| W | ||
| WGAN | Wasserstein GAN | |
| W | weight | 權重 |
| word embedding | 詞嵌入 | |
| WSD | word sense disambiguation | 詞義消歧 |
| X | ||
| Y | ||
| Z | ||
| ZSL | zero-shot learning | 零次學習 |
| zero-data learning | 零資料學習 |
參考文獻
[1]機器學習.Tom M.Mitchell