摘要
人工智能术语翻译第四部分，包括I、J、K、L开头的词汇！
M
| 英文术语 | 中文翻译 | 常用缩写 | 备注 |
|---|
| Machine Learning Model | 机器学习模型 | | |
| Machine Learning | 机器学习 | ML | 机器学习 |
| Machine Translation | 机器翻译 | MT | |
| Macro Average | 宏平均 | | |
| Macro-F1 | 宏F1 | | |
| Macro-P | 宏查准率 | | |
| Macron-R | 宏查全率 | | |
| Mahalanobis Distance | 马哈拉诺比斯距离 | | |
| Main Diagonal | 主对角线 | | |
| Majority Voting | 绝对多数投票 | | |
| Majority Voting Rule | 多数表决规则 | | |
| Manhattan Distance | 曼哈顿距离 | | |
| Manifold | 流形 | | |
| Manifold Assumption | 流形假设 | | |
| Manifold Learning | 流形学习 | | |
| Manifold Tangent Classifier | 流形正切分类器 | | |
| Margin | 间隔 | | 统计 |
| Margin Theory | 间隔理论 | | |
| Marginal Distribution | 边缘分布 | | |
| Marginal Independence | 边缘独立性 | | |
| Marginal Likelihood | 边缘似然函数 | | |
| Marginal Probability Distribution | 边缘概率分布 | | |
| Marginalization | 边缘化 | | |
| Markov Blanket | 马尔可夫毯 | | |
| Markov Chain | 马尔可夫链 | | |
| Markov Chain Monte Carlo | 马尔可夫链蒙特卡罗 | MCMC | |
| Markov Decision Process | 马尔可夫决策过程 | MDP | |
| Markov Network | 马尔可夫网络 | | |
| Markov Process | 马尔可夫过程 | | |
| Markov Property | 马尔可夫性质 | | |
| Markov Random Field | 马尔可夫随机场 | MRF | |
| Mask | 掩码 | | |
| Mask Language Modeling | 掩码语言模型化 | | |
| Masked Self-Attention | 掩蔽自注意力 | | |
| Mathematical Optimization | 数学优化 | | |
| Matrix | 矩阵 | | |
| Matrix Calculus | 矩阵微积分 | | |
| Matrix Completion | 矩阵补全 | | |
| Matrix Decomposition | 矩阵分解 | | |
| Matrix Inversion | 逆矩阵 | | |
| Matrix Product | 矩阵乘积 | | |
| Max Norm | 最大范数 | | |
| Max Pooling | 最大汇聚 | | |
| Maxima | 极大值 | | |
| Maximal Clique | 最大团 | | |
| Maximization | 极大 | | |
| Maximization Step | M步 | | |
| Maximization-Maximization Algorithm | 极大-极大算法 | | |
| Maximum A Posteriori | 最大后验 | | |
| Maximum A Posteriori Estimation | 最大后验估计 | MAP | |
| Maximum Entropy Model | 最大熵模型 | | |
| Maximum Likelihood | 极大似然 | | |
| Maximum Likelihood Estimation | 极大似然估计 | MLE | |
| Maximum Likelihood Method | 极大似然法 | | |
| Maximum Margin | 最大间隔 | | |
| Maximum Mean Discrepancy | 最大平均偏差 | | |
| Maximum Posterior Probability Estimation | 最大后验概率估计 | MAP | |
| Maximum Weighted Spanning Tree | 最大带权生成树 | | |
| Maxout | Maxout | | |
| Maxout Unit | Maxout单元 | | |
| Mean | 均值 | | |
| Mean Absolute Error | 平均绝对误差 | | |
| Mean And Covariance RBM | 均值和协方差RBM | | |
| Mean Filed | 平均场 | | |
| Mean Filter | 均值滤波 | | |
| Mean Pooling | 平均汇聚 | | |
| Mean Product of Student t-Distribution | 学生 t 分布均值乘积 | | |
| Mean Squared Error | 均方误差 | | |
| Mean-Covariance Restricted Boltzmann Machine | 均值-协方差受限玻尔兹曼机 | | |
| Mean-Field | 平均场 | | |
| Meanfield | 均匀场 | | |
| Measure Theory | 测度论 | | |
| Measure Zero | 零测度 | | |
| Median | 中位数 | | |
| Memory | 记忆 | | |
| Memory Augmented Neural Network | 记忆增强神经网络 | MANN | |
| Memory Capacity | 记忆容量 | | |
| Memory Cell | 记忆元 | | |
| Memory Network | 记忆网络 | MN | |
| Memory Segment | 记忆片段 | | |
| Mercer Kernel | Mercer 核 | | |
| Message | 消息 | | |
| Message Passing | 消息传递 | | |
| Message Passing Neural Network | 消息传递神经网络 | MPNN | |
| Meta-Learner | 元学习器 | | |
| Meta-Learning | 元学习 | | |
| Meta-Optimization | 元优化 | | |
| Meta-Rule | 元规则 | | |
| Metric | 指标 | | |
| Metric Learning | 度量学习 | | |
| Micro Average | 微平均 | | |
| Micro-F1 | 微F1 | | |
| Micro-P | 微査准率 | | |
| Micro-R | 微查全率 | | |
| Min-Max Normalization | 最小最大值规范化 | | |
| Mini-Batch Gradient | 小批量梯度 | | |
| Mini-Batch Gradient Descent | 小批量梯度下降法 | | |
| Mini-Batch SGD | 小批次随机梯度下降 | | |
| Minibatch | 小批量 | | |
| Minibatch Stochastic | 小批量随机 | | |
| Minima | 极小值 | | |
| Minimal Description Length | 最小描述长度 | MDL | |
| Minimax Game | 极小极大博弈 | | |
| Minimum | 极小点 | | |
| Minkowski Distance | 闵可夫斯基距离 | | |
| Misclassification Cost | 误分类代价 | | |
| Mixing | 混合 | | |
| Mixing Time | 混合时间 | | |
| Mixture Density Network | 混合密度网络 | | |
| Mixture Distribution | 混合分布 | | |
| Mixture of Experts | 混合专家模型 | | |
| Mixture-of-Gaussian | 高斯混合 | | |
| Modality | 模态 | | |
| Mode | 峰值 | | |
| Model | 模型 | | |
| Model Averaging | 模型平均 | | |
| Model Collapse | 模型坍塌 | | |
| Model Complexity | 模型复杂度 | | |
| Model Compression | 模型压缩 | | |
| Model Identifiability | 模型可辨识性 | | |
| Model Parallelism | 模型并行 | | |
| Model Parameter | 模型参数 | | |
| Model Predictive Control | 模型预测控制 | MPC | |
| Model Selection | 模型选择 | | |
| Model-Agnostic Meta-Learning | 模型无关的元学习 | MAML | |
| Model-Based Learning | 有模型学习 | | |
| Model-Based Reinforcement Learning | 基于模型的强化学习 | | |
| Model-Free Learning | 免模型学习 | | |
| Model-Free Reinforcement Learning | 模型无关的强化学习 | | |
| Moment | 矩 | | |
| Moment Matching | 矩匹配 | | |
| Momentum | 动量 | | |
| Momentum Method | 动量法 | | |
| Monte Carlo | 蒙特卡罗 | | |
| Monte Carlo Estimate | 蒙特卡罗估计 | | |
| Monte Carlo Integration | 蒙特卡罗积分 | | |
| Monte Carlo Method | 蒙特卡罗方法 | | |
| Moore’s Law | 摩尔定律 | | |
| Moore-Penrose Pseudoinverse | Moore-Penrose 伪逆 | | |
| Moral Graph | 端正图/道德图 | | |
| Moralization | 道德化 | | |
| Most General Unifier | 最一般合一置换 | | |
| Moving Average | 移动平均 | MA | |
| Multi-Armed Bandit Problem | 多臂赌博机问题 | | |
| Multi-Class Classification | 多分类 | | |
| Multi-Classifier System | 多分类器系统 | | |
| Multi-Document Summarization | 多文档摘要 | | |
| Multi-Head Attention | 多头注意力 | | |
| Multi-Head Self-Attention | 多头自注意力 | | |
| Multi-Hop | 多跳 | | |
| Multi-Kernel Learning | 多核学习 | | |
| Multi-Label Classification | 多标签分类 | | |
| Multi-Label Learning | 多标记学习 | | |
| Multi-Layer Feedforward Neural Networks | 多层前馈神经网络 | | |
| Multi-Layer Perceptron | 多层感知机 | MLP | |
| Multi-Nominal Logistic Regression Model | 多项对数几率回归模型 | | |
| Multi-Prediction Deep Boltzmann Machine | 多预测深度玻尔兹曼机 | | |
| Multi-Response Linear Regression | 多响应线性回归 | MLR | |
| Multi-View Learning | 多视图学习 | | |
| Multicollinearity | 多重共线性 | | |
| Multimodal | 多峰值 | | |
| Multimodal Learning | 多模态学习 | | |
| Multinomial Distribution | 多项分布 | | |
| Multinoulli Distribution | Multinoulli分布 | | |
| Multinoulli Output Distribution | Multinoulli输出分布 | | |
| Multiple Dimensional Scaling | 多维缩放 | | |
| Multiple Linear Regression | 多元线性回归 | MLR | 统计 |
| Multitask Learning | 多任务学习 | | |
| Multivariate Decision Tree | 多变量决策树 | | |
| Multivariate Gaussian Distribution | 多元高斯分布 | | |
| Multivariate Normal Distribution | 多元正态分布 | | |
| Mutual Information | 互信息 | | |
| Machine-Readable Data | 机器可读的数据 | | |
| Mae | 平均绝对误差 | MAE | |
| Mahalanobis Distances | 马氏距离 | | 统计 |
| Matrices | 矩阵 | | 数学 |
| Matthews Correlation Coefficient | 马修斯相关系数 | MCC | |
| Maximum Likelihood Methods | 最大似然法 | | 统计 |
| Maximum Likelihood Procedures | 最大似然估计法 | | 统计 |
| MCTS Method | 蒙特卡洛树搜索方法 | | |
| Mean-Squared Error | 均方误差 | | 统计、机器学习 |
| Mechanical Sympathy | 机械同感，软硬件协同编程 | | |
| Merging | 合并 | | |
| Message Passing Neural Networks | 消息传递神经网络 | MPNNS | |
| Microarray Data | 微阵列数据 | | |
| Mini Batch | 小批次 | | |
| Mining | 挖掘 | | |
| Mining Out | 挖掘 | | |
| Missing Values | 缺失值 | | 统计 |
| ML Algorithm | 机器学习算法 | | |
| ML Modelling | 机器学习建模 | | |
| ML Potentials | 机器学习势能 | | |
| ML-Driven | 机器学习驱动的 | | |
| ML-Driven Optimization | 机器学习驱动的最优化 | | |
| MLP Neural Model | 多层感知机神经模型 | | |
| Model Construction | 模型构建 | | |
| Model Evaluation | 模型评估 | | |
| Model Performance | 模型性能 | | |
| Model Statistics | 模型统计 | | |
| Model Training | 模型训练 | | 机器学习 |
| Model Validation | 模型验证 | | |
| Model-Based Iterative Reconstruction | 基于模型的迭代重建 | MBIR | |
| Model-Construction | 模型构建 | | |
| Modelling Scenario | 建模场景 | | |
| Molecular Graph Theory | 分子图论 | | |
| Molecular Modelling | 分子建模 | | |
| Monte Carlo Tree Search | 蒙特卡洛树搜索 | MCTS | 数学 |
| Moore’S Law | 摩尔定律 | | 计算机 |
| Multi-Agent Control System | 多智能体控制系统 | | |
| Multi-Core Desktop Computer | 多核台式计算机 | | 计算机 |
| Multi-Dimensional Big Data Analysis | 多维度大数据分析 | | |
| Multi-Layer Feed-Forward | 多层前馈 | MLFF | |
| Multi-Objective Genetic Algorithm | 多目标遗传算法 | MOGA | |
| Multi-Objective Optimization | 多目标优化 | | 机器学习 |
| Multi-Reaction Synthesis | 多反应合成 | | |
| Multilayer Perceptron | 多层感知机 | | |
| Multivariate Regression | 多变量回归 | | |
N
| 英文术语 | 中文翻译 | 常用缩写 | 备注 |
|---|
| N-Gram | N元 | | |
| N-Gram Feature | N元特征 | | |
| N-Gram Model | N元模型 | | |
| Naive Bayes Algorithm | 朴素贝叶斯算法 | | |
| Naive Bayes Classifier | 朴素贝叶斯分类器 | | |
| Naive Bayes | 朴素贝叶斯 | NB | |
| Named Entity Recognition | 命名实体识别 | | |
| Narrow Convolution | 窄卷积 | | |
| Nash Equilibrium | 纳什均衡 | | |
| Nash Reversion | 纳什回归 | | |
| Nats | 奈特 | | |
| Natural Exponential Decay | 自然指数衰减 | | |
| Natural Language Generation | 自然语言生成 | NLG | |
| Natural Language Processing | 自然语言处理 | NLP | 机器学习 |
| Nearest Neighbor | 最近邻 | | |
| Nearest Neighbor Classifier | 最近邻分类器 | | |
| Nearest Neighbor Graph | 最近邻图 | | |
| Nearest Neighbor Regression | 最近邻回归 | | |
| Nearest-Neighbor Search | 最近邻搜索 | | |
| Negative Class | 负类 | | |
| Negative Correlation | 负相关法 | | |
| Negative Definite | 负定 | | |
| Negative Log Likelihood | 负对数似然函数 | | |
| Negative Part Function | 负部函数 | | |
| Negative Phase | 负相 | | |
| Negative Sample | 负例 | | |
| Negative Sampling | 负采样 | | |
| Negative Semidefinite | 半负定 | | |
| Neighbourhood Component Analysis | 近邻成分分析 | NCA | |
| Nesterov Accelerated Gradient | Nesterov加速梯度 | NAG | |
| Nesterov Momentum | Nesterov动量法 | | |
| Net Activation | 净活性值 | | |
| Net Input | 净输入 | | |
| Network | 网络 | | |
| Network Capacity | 网络容量 | | |
| Neural Architecture Search | 神经架构搜索 | NAS | |
| Neural Auto-Regressive Density Estimator | 神经自回归密度估计器 | | |
| Neural Auto-Regressive Network | 神经自回归网络 | | |
| Neural Language Model | 神经语言模型 | | |
| Neural Machine Translation | 神经机器翻译 | | |
| Neural Model | 神经模型 | | |
| Neural Network | 神经网络 | NN | |
| Neural Turing Machine | 神经图灵机 | NTM | |
| Neurodynamics | 神经动力学 | | |
| Neuromorphic Computing | 神经形态计算 | | |
| Neuron | 神经元 | | |
| Newton Method | 牛顿法 | | |
| No Free Lunch Theorem | 没有免费午餐定理 | NFL | |
| Node | 结点 | | |
| Noise | 噪声 | | |
| Noise Distribution | 噪声分布 | | |
| Noise-Contrastive Estimation | 噪声对比估计 | NCE | |
| Nominal Attribute | 列名属性 | | |
| Non-Autoregressive Process | 非自回归过程 | | |
| Non-Convex Optimization | 非凸优化 | | |
| Non-Informative Prior | 无信息先验 | | |
| Non-Linear Model | 非线性模型 | | |
| Non-Linear Oscillation | 非线性振荡 | | |
| Non-Linear Support Vector Machine | 非线性支持向量机 | | |
| Non-Metric Distance | 非度量距离 | | |
| Non-Negative Matrix Factorization | 非负矩阵分解 | NMF | |
| Non-Ordinal Attribute | 无序属性 | | |
| Non-Parametric | 非参数 | | |
| Non-Parametric Model | 非参数化模型 | | |
| Non-Probabilistic Model | 非概率模型 | | |
| Non-Saturating Game | 非饱和博弈 | | |
| Non-Separable | 不可分 | | |
| Nonconvex | 非凸 | | |
| Nondistributed | 非分布式 | | |
| Nondistributed Representation | 非分布式表示 | | |
| Nonlinear Autoregressive With Exogenous Inputs Model | 有外部输入的非线性自回归模型 | NARX | |
| Nonlinear Conjugate Gradients | 非线性共轭梯度 | | |
| Nonlinear Independent Components Estimation | 非线性独立成分估计 | | |
| Nonlinear Programming | 非线性规划 | | |
| Nonparametric Density Estimation | 非参数密度估计 | | |
| Norm | 范数 | | |
| Norm-Preserving | 范数保持性 | | |
| Normal Distribution | 正态分布 | | |
| Normal Equation | 正规方程 | | |
| Normalization | 规范化 | | 统计、机器学习 |
| Normalization Factor | 规范化因子 | | |
| Normalized | 规范化的 | | |
| Normalized Initialization | 标准初始化 | | |
| Nuclear Norm | 核范数 | | |
| Null Space | 零空间 | | |
| Number of Epochs | 轮数 | | |
| Numerator Layout | 分子布局 | | |
| Numeric Value | 数值 | | |
| Numerical Attribute | 数值属性 | | |
| Numerical Differentiation | 数值微分 | | |
| Numerical Method | 数值方法 | | |
| Numerical Optimization | 数值优化 | | |
| N-Dimensional Space | N维空间 | | |
| Naive Bayesian | 朴素贝叶斯 | | 统计 |
| Naive Bayesian Methods | 朴素贝叶斯方法 | | 统计 |
| Named Entity Recognition，NER | 命名实体识别 | NER | |
| Nearest Neighbors | 近邻 | | |
| Nearest Neighbour Model | 近邻模型 | | |
| Negative Predictive Value | 阴性预测值 | NPV | |
| Network Architecture | 网络结构 | | 机器学习 |
| Network Geometry | 网络几何 | | |
| Neural Turing Machines | 神经图灵机 | NTM | |
| Neural-Network-Based Function | 基于神经网络的函数 | | |
| Neurons | 神经元 | | 机器学习 |
| Nuclear Magnetic Resonance | 核磁共振 | NMR | |
| Noise Filters | 噪声过滤器 | | |
| Noise-Free | 无噪的 | | |
| Non-Linear | 非线性 | | 数学、统计 |
| Non-Linear Correlation | 非线性相关 | | 统计 |
| Non-Linearity | 非线性 | | |
| Non-Parametric Algorithm | 非参数化学习算法 | | |
| Non-Safety-Critical Applications | 非安全关键型应用 | | |
| Non-Steady-State | 非稳态 | | |
| Non-Stochastic | 非随机的 | | |
| Non-Template | 非模板 | | |
| Non-Template Methods | 非模板方法 | | |
| Non-Zero Weight | 非零权重 | | |
O
| 英文术语 | 中文翻译 | 常用缩写 | 备注 |
|---|
| Object Detection | 目标检测 | | |
| Object Recognition | 对象识别 | | |
| Objective | 目标 | | |
| Objective Function | 目标函数 | | |
| Oblique Decision Tree | 斜决策树 | | |
| Observable Variable | 观测变量 | | |
| Observation Sequence | 观测序列 | | |
| Occam’s Razor | 奥卡姆剃刀 | | 机器学习 |
| Odds | 几率 | | |
| Off-Policy | 异策略 | | |
| Offline Inference | 离线推断 | | |
| Offset | 偏移量 | | |
| Offset Vector | 偏移向量 | | |
| On-Policy | 同策略 | | |
| One-Shot Learning | 单试学习 | | |
| One-Dependent Estimator | 独依赖估计 | ODE | |
| One-Hot | 独热 | | |
| Online | 在线 | | |
| Online Inference | 在线推断 | | |
| Online Learning | 在线学习 | | |
| Operation | 操作 | | |
| Operator | 运算符 | | |
| Optimal Capacity | 最佳容量 | | |
| Optimization | 最优化 | | |
| Optimization Landscape | 优化地形 | | |
| Optimizer | 优化器 | | |
| Ordered Rule | 带序规则 | | |
| Ordinal Attribute | 有序属性 | | |
| Origin | 原点 | | |
| Orthogonal | 正交 | | 数学 |
| Orthogonal Initialization | 正交初始化 | | |
| Orthogonal Matrix | 正交矩阵 | | |
| Orthonormal | 标准正交 | | |
| Out-Of-Bag Estimate | 包外估计 | | |
| Outer Product | 外积 | | |
| Outlier | 异常点 | | |
| Output | 输出 | | |
| Output Gate | 输出门 | | |
| Output Layer | 输出层 | | 机器学习 |
| Output Smearing | 输出调制法 | | |
| Output Space | 输出空间 | | |
| Over-Parameterized | 过度参数化 | | |
| Overcomplete | 过完备 | | |
| Overestimation | 过估计 | | |
| Overfitting | 过拟合 | | 机器学习 |
| Overfitting Regime | 过拟合机制 | | |
| Overflow | 上溢 | | |
| Oversampling | 过采样 | | |
| On-The-Fly Optimization | 运行中优化 | | 计算机 |
| One-Hot Vector | 独热向量 | | 整个矢量中之后一个数为1 其余为0 |
| Open-Source | 开源 | | 软件工程 |
| Open-Source Dataset | 开源数据集 | | 机器学习 |
P
| 英文术语 | 中文翻译 | 常用缩写 | 备注 |
|---|
| PAC Learning | PAC学习 | | |
| Pac-Learnable | PAC可学习 | | |
| Padding | 填充 | | |
| Paired t -Test | 成对 t 检验 | | |
| Pairwise | 成对型 | | |
| Pairwise Markov Property | 成对马尔可夫性 | | |
| Parallel Distributed Processing | 分布式并行处理 | PDP | |
| Parallel Tempering | 并行回火 | | |
| Parameter | 参数 | | |
| Parameter Estimation | 参数估计 | | |
| Parameter Server | 参数服务器 | | |
| Parameter Sharing | 参数共享 | | |
| Parameter Space | 参数空间 | | |
| Parameter Tuning | 调参 | | 机器学习 |
| Parametric Case | 有参情况 | | |
| Parametric Density Estimation | 参数密度估计 | | |
| Parametric Model | 参数化模型 | | |
| Parametric ReLU | 参数化修正线性单元/参数化整流线性单元 | PReLU | |
| Parse Tree | 解析树 | | |
| Part-Of-Speech Tagging | 词性标注 | | |
| Partial Derivative | 偏导数 | | |
| Partially Observable Markov Decision Processes | 部分可观测马尔可夫决策过程 | POMDP | |
| Particle Swarm Optimization | 粒子群优化算法 | PSO | |
| Partition | 划分 | | |
| Partition Function | 配分函数 | | |
| Path | 路径 | | |
| Pattern | 模式 | | |
| Pattern Recognition | 模式识别 | PR | |
| Penalty Term | 罚项 | | |
| Perceptron | 感知机 | | 机器学习 |
| Performance Measure | 性能度量 | | |
| Periodic | 周期的 | | |
| Permutation Invariant | 置换不变性 | | |
| Perplexity | 困惑度 | | |
| Persistent Contrastive Divergence | 持续性对比散度 | | |
| Phoneme | 音素 | | |
| Phonetic | 语音 | | |
| Pictorial Structure | 图形结构 | | |
| Piecewise | 分段 | | |
| Piecewise Constant Decay | 分段常数衰减 | | |
| Pipeline | 流水线 | | |
| Plate Notation | 板块表示 | | |
| Plug And Play Generative Network | 即插即用生成网络 | | |
| Plurality Voting | 相对多数投票 | | |
| Point Estimator | 点估计 | | |
| Pointer Network | 指针网络 | | |
| Polarity Detection | 极性检测 | | |
| Policy | 策略 | | |
| Policy Evaluation | 策略评估 | | |
| Policy Gradient | 策略梯度 | | |
| Policy Improvement | 策略改进 | | |
| Policy Iteration | 策略迭代 | | |
| Policy Search | 策略搜索 | | |
| Polynomial Basis Function | 多项式基函数 | | |
| Polynomial Kernel Function | 多项式核函数 | | |
| Polysemy | 一词多义性 | | |
| Pool | 汇聚 | | |
| Pooling | 汇聚 | | |
| Pooling Function | 汇聚函数 | | |
| Pooling Layer | 汇聚层 | | |
| Poor Conditioning | 病态条件 | | |
| Position Embedding | 位置嵌入 | | |
| Positional Encoding | 位置编码 | | |
| Positive Class | 正类 | | |
| Positive Definite | 正定 | | |
| Positive Definite Kernel Function | 正定核函数 | | |
| Positive Definite Matrix | 正定矩阵 | | |
| Positive Part Function | 正部函数 | | |
| Positive Phase | 正相 | | |
| Positive Recurrent | 正常返的 | | |
| Positive Sample | 正例 | | |
| Positive Semidefinite | 半正定 | | |
| Positive-Semidefinite Matrix | 半正定矩阵 | | |
| Post-Hoc Test | 后续检验 | | |
| Post-Pruning | 后剪枝 | | |
| Posterior Distribution | 后验分布 | | |
| Posterior Inference | 后验推断 | | |
| Posterior Probability | 后验概率 | | |
| Potential Function | 势函数 | | |
| Power Method | 幂法 | | |
| PR Curve | P-R曲线 | | |
| Pre-Trained Initialization | 预训练初始化 | | |
| Pre-Training | 预训练 | | |
| Precision | 查准率/准确率 | | 数学、HPC |
| Precision Matrix | 精度矩阵 | | |
| Predictive Sparse Decomposition | 预测稀疏分解 | | |
| Prepruning | 预剪枝 | | |
| Pretrained Language Model | 预训练语言模型 | | |
| Primal Problem | 主问题 | | |
| Primary Visual Cortex | 初级视觉皮层 | | |
| Principal Component Analysis | 主成分分析 | PCA | |
| Principle Of Multiple Explanations | 多释原则 | | |
| Prior | 先验 | | |
| Prior Knowledge | 先验知识 | | 统计 |
| Prior Probability | 先验概率 | | |
| Prior Probability Distribution | 先验概率分布 | | |
| Prior Pseudo-Counts | 伪计数 | | |
| Prior Shift | 先验偏移 | | |
| Priority Rule | 优先级规则 | | |
| Probabilistic Context-Free Grammar | 概率上下文无关文法 | | |
| Probabilistic Density Estimation | 概率密度估计 | | |
| Probabilistic Generative Model | 概率生成模型 | | |
| Probabilistic Graphical Model | 概率图模型 | PGM | |
| Probabilistic Latent Semantic Analysis | 概率潜在语义分析 | PLSA | |
| Probabilistic Latent Semantic Indexing | 概率潜在语义索引 | PLSI | |
| Probabilistic Model | 概率模型 | | |
| Probabilistic PCA | 概率PCA | | |
| Probabilistic Undirected Graphical Model | 概率无向图模型 | | |
| Probability | 概率 | | |
| Probability Density Function | 概率密度函数 | PDF | |
| Probability Distribution | 概率分布 | | 统计 |
| Probability Mass Function | 概率质量函数 | | |
| Probability Model Estimation | 概率模型估计 | | |
| Probably Approximately Correct | 概率近似正确 | PAC | |
| Product of Expert | 专家之积 | | |
| Product Rule | 乘法法则 | | |
| Properly PAC Learnable | 恰PAC可学习 | | |
| Proportional | 成比例 | | |
| Proposal Distribution | 提议分布 | | |
| Propositional Atom | 原子命题 | | |
| Propositional Rule | 命题规则 | | |
| Prototype-Based Clustering | 原型聚类 | | |
| Proximal Gradient Descent | 近端梯度下降 | PGD | |
| Pruning | 剪枝 | | |
| Pseudo-Label | 伪标记 | | |
| Pseudolikelihood | 伪似然 | | |
| Predicted Label | 预测值 | | 机器学习 |
| Prediction | 预测 | | 机器学习 |
| Prediction Accuracy | 预测准确率 | | 机器学习 |
| Predictor | 预测器/决策函数 | | 机器学习 |
| Protein Folding | 蛋白折叠 | | 生物 |
