人工智能术语翻译（三）
【摘要】 @[toc] 摘要人工智能术语翻译第三部分，包括I、J、K、L开头的词汇！ I英文术语中文翻译常用缩写备注I.I.D. Assumption独立同分布假设Identically Distributed同分布的Identifiable可辨认的Identity Function恒等函数Identity Mapping恒等映射Identity Matrix单位矩阵Ill Conditioning病...
@[toc]
摘要
人工智能术语翻译第三部分，包括I、J、K、L开头的词汇！
I
| 英文术语 | 中文翻译 | 常用缩写 | 备注 |
|---|---|---|---|
| I.I.D. Assumption | 独立同分布假设 | ||
| Identically Distributed | 同分布的 | ||
| Identifiable | 可辨认的 | ||
| Identity Function | 恒等函数 | ||
| Identity Mapping | 恒等映射 | ||
| Identity Matrix | 单位矩阵 | ||
| Ill Conditioning | 病态 | ||
| Ill-Formed Problem | 病态问题 | ||
| Image | 图像 | ||
| Image Restoration | 图像还原 | ||
| Imitation Learning | 模仿学习 | ||
| Immorality | 不道德 | ||
| Imperfect Information | 不完美信息 | ||
| Implicit Density Model | 隐式密度模型 | ||
| Import | 导入 | ||
| Importance Sampling | 重要性采样 | ||
| Improved Iterative Scaling | 改进的迭代尺度法 | IIS | |
| Incomplete-Data | 不完全数据 | ||
| Incremental Learning | 增量学习 | ||
| Indefinite Integral | 不定积分 | ||
| Independence | 独立 | ||
| Independent | 相互独立的 | ||
| Independent and Identically Distributed | 独立同分布 | I.I.D. | |
| Independent Component Analysis | 独立成分分析 | ICA | |
| Independent Subspace Analysis | 独立子空间分析 | ||
| Index of Matrix | 索引 | ||
| Indicator Function | 指示函数 | ||
| Individual Learner | 个体学习器 | ||
| Induction | 归纳 | ||
| Inductive Bias | 归纳偏好 | ||
| Inductive Learning | 归纳学习 | ||
| Inductive Logic Programming | 归纳逻辑程序设计 | ILP | |
| Inductive Transfer Learning | 归纳迁移学习 | ||
| Inequality Constraint | 不等式约束 | ||
| Inference | 推断 | ||
| Infinite | 无限 | ||
| Infinitely Exchangeable | 无限可交换 | ||
| Information Divergence | 信息散度 | ||
| Information Entropy | 信息熵 | ||
| Information Gain | 信息增益 | 统计 | |
| Information Gain Ratio | 信息增益比 | 统计 | |
| Information Retrieval | 信息检索 | ||
| Information Theory | 信息论 | ||
| Inner Product | 内积 | ||
| Input | 输入 | ||
| Input Distribution | 输入分布 | ||
| Input Gate | 输入门 | ||
| Input Layer | 输入层 | ||
| Input Space | 输入空间 | ||
| Insensitive Loss | 不敏感损失 | ||
| Instance | 示例 | ||
| Instance Segmentation | 实例分割 | ||
| Integer Linear Programming | 整数线性规划 | ILP | |
| Integer Programming | 整数规划 | ||
| Integration | 积分 | ||
| Inter-Cluster Similarity | 簇间相似度 | ||
| Internal Covariate Shift | 内部协变量偏移 | ||
| Internal Node | 内部结点 | ||
| International Conference For Machine Learning | 国际机器学习大会 | ICML | |
| Intervention Query | 干预查询 | ||
| Intra-Attention | 内部注意力 | ||
| Intra-Cluster Similarity | 簇内相似度 | ||
| Intrinsic Value | 固有值 | ||
| Invariance | 不变性 | ||
| Invariant | 不变 | ||
| Inverse Matrix | 逆矩阵 | ||
| Inverse Reinforcement Learning | 逆强化学习 | IRL | |
| Inverse Resolution | 逆归结 | ||
| Inverse Time Decay | 逆时衰减 | ||
| Invert | 求逆 | ||
| Irreducible | 不可约的 | ||
| Irrelevant Feature | 无关特征 | ||
| Isometric Mapping | 等度量映射 | Isomap | |
| Isotonic Regression | 等分回归 | ||
| Isotropic | 各向同性 | ||
| Isotropic Gaussian Distribution | 各向同性高斯分布 | ||
| Iteration | 迭代 | 数学、机器学习 | |
| Iterative Dichotomiser | 迭代二分器 | ||
| Id3 Algorithm | Id3 算法 | ||
| Image And Speech Recognition | 图像和语音识别 | ||
| Image Classification | 图像分类 | ||
| Image Classifier | 图像分类器 | ||
| Image Recognition | 图像识别 | 机器学习 | |
| Informative Priors | 信息先验 | ||
| Input-Output Pairs | 输入输出对 | ||
| Instance-Based | 基于实例的 | ||
| Intelligent Machine | 智能机器 | ||
| Intermediate Neurons | 中间神经元 | 机器学习 | |
| Internet Of Things | 物联网 | IoT | |
| Interpolation Coordinate | 插值坐标 | ||
| Interpretability | 可解释性 | ||
| Inverse Neural Modeling | 逆神经建模 | INN | |
| Inverse Neural Network Modeling | 逆神经网络建模 | ||
| Iterative Learning | 迭代学习 |
J
| 英文术语 | 中文翻译 | 常用缩写 | 备注 |
|---|---|---|---|
| Jacobian | 雅克比 | ||
| Jacobian Matrix | 雅可比矩阵 | ||
| Jensen Inequality | Jensen不等式 | ||
| Jensen-Shannon Divergence | JS散度 | JSD | |
| Joint Probability Density Function | 联合概率密度函数 | ||
| Joint Probability Distribution | 联合概率分布 | ||
| Junction Tree Algorithm | 联合树算法 | ||
| Joint Distribution | 联合分布 | ||
| Jordan-Elman Neural Networks | Jordan-Elman 神经网络 |
K
| 英文术语 | 中文翻译 | 常用缩写 | 备注 |
|---|---|---|---|
| K-Armed Bandit Problem | k-摇臂老虎机 | ||
| K-Fold Cross Validation | k 折交叉验证 | K-FOLD CV | 统计 |
| K-Means Clustering | k-均值聚类 | ||
| K-Nearest Neighbor Classifier | k-近邻分类器 | ||
| K-Nearest Neighbor Method | k-近邻 | K-NN | 统计 |
| Karush-Kuhn-Tucker Condition | KKT条件 | ||
| Karush–Kuhn–Tucker | Karush–Kuhn–Tucker | ||
| Kd Tree | Kd 树 | ||
| Kernel Density Estimation | 核密度估计 | ||
| Kernel Function | 核函数 | ||
| Kernel Machine | 核机器 | ||
| Kernel Matrix | 核矩阵 | ||
| Kernel Method | 核方法 | 机器学习 | |
| Kernel Regression | 核回归 | ||
| Kernel Trick | 核技巧 | ||
| Kernelized | 核化 | ||
| Kernelized Linear Discriminant Analysis | 核线性判别分析 | KLDA | |
| Kernelized PCA | 核主成分分析 | KPCA | |
| Key-Value Store | 键-值数据库 | ||
| KL Divergence | KL散度 | ||
| Knowledge | 知识 | ||
| Knowledge Base | 知识库 | ||
| Knowledge Distillation | 知识蒸馏 | ||
| Knowledge Engineering | 知识工程 | ||
| Knowledge Graph | 知识图谱 | ||
| Knowledge Representation | 知识表征 | ||
| Kronecker Product | Kronecker积 | ||
| Krylov Method | Krylov方法 | ||
| K Clusters | K聚类 | ||
| K Nearest Points | K 最近点 | 统计 | |
| K-1 Folds | K-1 折 | ||
| K-Edge (O-K Edge) | K-边缘（O-K 边缘） | ||
| K-Means | K-均值 | 统计 | |
| Kendall’S Tau | 肯德尔等级相关系数 | ||
| Kernel Ridge Regression | 核岭回归 | KRR | |
| Kernels | 内核 | ||
| Kinetic Curve | 动力学曲线 | ||
| KNN Model | K 近邻模型 | ||
| Knowledge Extraction | 知识提取 | ||
| Knowledge Gradient | 知识梯度 | KG |
L
| 英文术语 | 中文翻译 | 常用缩写 | 备注 |
|---|---|---|---|
| L-BFGS | L-BFGS | ||
| Label | 标签/标记 | ||
| Label Propagation | 标记传播 | ||
| Label Smoothing | 标签平滑 | ||
| Label Space | 标记空间 | ||
| Labeled | 标注 | ||
| Lagrange Dual Problem | 拉格朗日对偶问题 | ||
| Lagrange Duality | 拉格朗日对偶性 | ||
| Lagrange Function | 拉格朗日函数 | ||
| Lagrange Multiplier | 拉格朗日乘子 | ||
| Language Model | 语言模型 | ||
| Language Modeling | 语言模型化 | ||
| Laplace Distribution | Laplace分布 | ||
| Laplace Smoothing | 拉普拉斯平滑 | ||
| Laplacian Correction | 拉普拉斯修正 | ||
| Large Learning Step | 大学习步骤 | ||
| Las Vegas Method | 拉斯维加斯方法 | ||
| Latent | 潜在 | ||
| Latent Dirichlet Allocation | 潜在狄利克雷分配 | LDA | |
| Latent Layer | 潜层 | ||
| Latent Semantic Analysis | 潜在语义分析 | LSA | |
| Latent Semantic Indexing | 潜在语义索引 | LSI | |
| Latent Variable | 潜变量/隐变量 | ||
| Law of Large Numbers | 大数定律 | ||
| Layer | 层 | ||
| Layer Normalization | 层规范化 | ||
| Layer-Wise | 逐层的 | ||
| Layer-Wise Adaptive Rate Scaling | 逐层适应率缩放 | LARS | |
| Layer-Wise Normalization | 逐层规范化 | ||
| Layer-Wise Pretraining | 逐层预训练 | ||
| Layer-Wise Training | 逐层训练 | ||
| Lazy Learning | 懒惰学习 | ||
| Leaf Node | 叶结点 | ||
| Leaky Lelu Function | 泄漏线性整流函数 | ||
| Leaky Relu | 泄漏修正线性单元/泄漏整流线性单元 | ||
| Leaky Unit | 渗漏单元 | ||
| Learned | 学成 | ||
| Learned Approximate Inference | 学习近似推断 | ||
| Learner | 学习器 | ||
| Learning | 学习 | ||
| Learning Algorithm | 学习算法 | ||
| Learning By Analogy | 类比学习 | ||
| Learning Rate | 学习率 | ||
| Learning Rate Annealing | 学习率退火 | ||
| Learning Rate Decay | 学习率衰减 | ||
| Learning Rate Warmup | 学习率预热 | ||
| Learning To Learn | 学习的学习 | ||
| Learning Vector Quantization | 学习向量量化 | LVQ | |
| Least General Generalization | 最小一般泛化 | ||
| Least Mean Squares | 最小均方 | LMS | |
| Least Square Method | 最小二乘法 | LSM | |
| Least Squares Regression Tree | 最小二乘回归树 | ||
| Leave-One-Out Cross Validation | 留一交叉验证 | ||
| Leave-One-Out | 留一法 | LOO | |
| Lebesgue-Integrable | 勒贝格可积 | ||
| Left Eigenvector | 左特征向量 | ||
| Left Singular Vector | 左奇异向量 | ||
| Leibniz’s Rule | 莱布尼兹法则 | ||
| Lifelong Learning | 终身学习 | ||
| Likelihood | 似然 | ||
| Line Search | 线搜索 | ||
| Linear Auto-Regressive Network | 线性自回归网络 | ||
| Linear Chain | 线性链 | ||
| Linear Chain Conditional Random Field | 线性链条件随机场 | ||
| Linear Classification Model | 线性分类模型 | ||
| Linear Classifier | 线性分类器 | ||
| Linear Combination | 线性组合 | 数学 | |
| Linear Dependence | 线性相关 | ||
| Linear Discriminant Analysis | 线性判别分析 | LDA | 统计、机器学习 |
| Linear Factor Model | 线性因子模型 | ||
| Linear Mapping | 线性映射 | ||
| Linear Model | 线性模型 | LR | 统计、机器学习 |
| Linear Programming | 线性规划 | ||
| Linear Regression | 线性回归 | 统计、数学 | |
| Linear Scaling Rule | 线性缩放规则 | ||
| Linear Scan | 线性扫描 | ||
| Linear Space | 线性空间 | ||
| Linear Support Vector Machine | 线性支持向量机 | ||
| Linear Support Vector Machine In Linearly Separable Case | 线性可分支持向量机 | ||
| Linear Threshold Units | 线性阈值单元 | ||
| Linear Transformation | 线性变换 | ||
| Linearly Independent | 线性无关 | ||
| Linearly Separable | 线性可分 | ||
| Linearly Separable Data Set | 线性可分数据集 | ||
| Link Analysis | 链接分析 | ||
| Link Function | 联系函数 | ||
| Link Prediction | 链接预测 | ||
| Link Table | 连接表 | ||
| Linkage | 连接 | ||
| Linked Importance Sampling | 链接重要采样 | ||
| Lipschitz | Lipschitz | ||
| Lipschitz Constant | Lipschitz常数 | ||
| Lipschitz Continuous | Lipschitz连续 | ||
| Liquid State Machine | 流体状态机 | ||
| Local Conditional Probability Distribution | 局部条件概率分布 | ||
| Local Constancy Prior | 局部不变性先验 | ||
| Local Contrast Normalization | 局部对比度规范化 | ||
| Local Curvature | 局部曲率 | ||
| Local Descent | 局部下降 | ||
| Local Invariances | 局部不变性 | ||
| Local Kernel | 局部核 | ||
| Local Markov Property | 局部马尔可夫性 | ||
| Local Maxima | 局部极大值 | ||
| Local Maximum | 局部极大点 | ||
| Local Minima | 局部极小 | ||
| Local Minimizer | 局部最小解 | ||
| Local Minimum | 局部极小 | ||
| Local Representation | 局部式表示/局部式表征 | ||
| Local Response Normalization | 局部响应规范化 | LRN | |
| Locally Linear Embedding | 局部线性嵌入 | LLE | |
| Log Likelihood | 对数似然函数 | ||
| Log Linear Model | 对数线性模型 | ||
| Log-Likelihood | 对数似然 | ||
| Log-Likelihood Loss Function | 对数似然损失函数 | ||
| Log-Linear Regression | 对数线性回归 | ||
| Logarithmic Loss Function | 对数损失函数 | ||
| Logarithmic Scale | 对数尺度 | ||
| Logistic Distribution | 对数几率分布 | ||
| Logistic Function | 对数几率函数 | ||
| Logistic Loss | 对率损失 | ||
| Logistic Regression | 对数几率回归 | LR | 统计、机器学习 |
| Logistic Sigmoid | 对数几率Sigmoid | ||
| Logit | 对数几率 | ||
| Long Short Term Memory | 长短期记忆 | LSTM | |
| Long Short-Term Memory Network | 长短期记忆网络 | LSTM | |
| Long-Term Dependencies Problem | 长程依赖问题 | ||
| Long-Term Dependency | 长期依赖 | ||
| Long-Term Memory | 长期记忆 | ||
| Loop | 环 | ||
| Loopy Belief Propagation | 环状信念传播 | LBP | |
| Loss | 损失 | ||
| Loss Function | 损失函数 | 机器学习 | |
| Low Rank Matrix Approximation | 低秩矩阵近似 | ||
| Lp Distance | Lp距离 | ||
| L1 And L2 Regularization | L1与L2正则化 | ||
| Laboratory Level | 实验室级别 | ||
| Language Processing | 语言处理 | ||
| Laplacian Prior | 拉普拉斯先验 | ||
| Large-Scale Data Storage | 大规模数据存储 | ||
| Lasers | 激光器 | ||
| Lasso Regression | 拉索回归 | ||
| LBP | 局部二值模式 | ||
| Least Absolute Shrinkage And Selection Operator | Lasso回归 | LASSO | |
| Least Square Support Vector Machine | 最小二乘支持向量机 | LSSVM | |
| Ligand-Field | 配位场 | ||
| Linear | 线性的 | 数学 | |
| Linear Dimension Reduction Methods | 线性降维方法 | ||
| Linear Vibronic Coupling Model | 线性振子耦合模型 | ||
| Local Recurrent | 本地卷积 | ||
| Logic And Heuristics Applied To Synthetic Analysis | LHASA 程序 | LHASA | |
| Long-Range Prediction | 长期预测 | ||
| Long-Range Prediction Models | 长期预测模型 | ||
| Long-Term Planning | 长期规划 | ||
| Long-Term Reward | 长期回报 |
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