人工智能术语翻译(六)
【摘要】 @[toc] 摘要人工智能术语翻译第六部分,包括U、V、W、X、Y、Z开头的词汇! U英文术语中文翻译常用缩写备注Ugly Duckling Theorem丑小鸭定理Unbiased无偏Unbiased Estimate无偏估计Unbiased Sample Variance无偏样本方差Unconstrained Optimization无约束优化Undercomplete欠完备Underd...
@[toc]
摘要
人工智能术语翻译第六部分,包括U、V、W、X、Y、Z开头的词汇!

U
| 英文术语 | 中文翻译 | 常用缩写 | 备注 |
|---|---|---|---|
| Ugly Duckling Theorem | 丑小鸭定理 | ||
| Unbiased | 无偏 | ||
| Unbiased Estimate | 无偏估计 | ||
| Unbiased Sample Variance | 无偏样本方差 | ||
| Unconstrained Optimization | 无约束优化 | ||
| Undercomplete | 欠完备 | ||
| Underdetermined | 欠定的 | ||
| Underestimation | 欠估计 | ||
| Underfitting | 欠拟合 | 机器学习 | |
| Underfitting Regime | 欠拟合机制 | ||
| Underflow | 下溢 | ||
| Underlying | 潜在 | ||
| Underlying Cause | 潜在成因 | ||
| Undersampling | 欠采样 | ||
| Understandability | 可理解性 | ||
| Undirected | 无向 | ||
| Undirected Graph | 无向图 | ||
| Undirected Graphical Model | 无向图模型 | ||
| Undirected Model | 无向模型 | ||
| Unequal Cost | 非均等代价 | ||
| Unfolded Graph | 展开图 | ||
| Unfolding | 展开 | ||
| Unidirectional Language Model | 单向语言模型 | ||
| Unification | 合一 | ||
| Uniform Distribution | 均匀分布 | ||
| Uniform Sampling | 均匀采样 | ||
| Uniform Stability | 均匀稳定性 | ||
| Unigram | 一元语法 | ||
| Unimodal | 单峰值 | ||
| Unit | 单元 | ||
| Unit Norm | 单位范数 | ||
| Unit Test | 单元测试 | ||
| Unit Variance | 单位方差 | ||
| Unit Vector | 单位向量 | ||
| Unit-Step Function | 单位阶跃函数 | ||
| Unitary Matrix | 酉矩阵 | ||
| Univariate Decision Tree | 单变量决策树 | ||
| Universal Approximation Theorem | 通用近似定理 | ||
| Universal Approximator | 通用近似器 | ||
| Universal Function Approximator | 通用函数近似器 | ||
| Unknown Token | 未知词元 | ||
| Unlabeled | 未标记 | ||
| Unnormalized Probability Function | 未规范化概率函数 | ||
| Unprojection | 反投影 | ||
| Unshared Convolution | 非共享卷积 | ||
| Unsupervised | 无监督 | ||
| Unsupervised Feature Learning | 无监督特征学习 | ||
| Unsupervised Layer-Wise Training | 无监督逐层训练 | ||
| Unsupervised Learning Algorithm | 无监督学习算法 | ||
| Unsupervised Learning | 无监督学习 | UL | |
| Unsupervised Pretraining | 无监督预训练 | ||
| Update Gate | 更新门 | ||
| Update Model Parameter | 迭代模型参数 | ||
| Upper Confidence Bounds | 上置信界限 | ||
| Upsampling | 上采样 |
V
| 英文术语 | 中文翻译 | 常用缩写 | 备注 |
|---|---|---|---|
| V-Structure | V型结构 | ||
| Valid | 有效 | ||
| Validation Set | 验证集 | ||
| Validity Index | 有效性指标 | ||
| Value Function | 价值函数 | ||
| Value Function Approximation | 值函数近似 | ||
| Value Iteration | 值迭代 | ||
| Vanishing And Exploding Gradient Problem | 梯度消失与爆炸问题 | ||
| Vanishing Gradient | 梯度消失 | ||
| Vanishing Gradient Problem | 梯度消失问题 | ||
| Vapnik-Chervonenkis Dimension | VC维 | ||
| Variable Elimination | 变量消去 | ||
| Variance | 方差 | ||
| Variance Reduction | 方差减小 | ||
| Variance Scaling | 方差缩放 | ||
| Variational Autoencoder | 变分自编码器 | VAE | |
| Variational Bayesian | 变分贝叶斯 | ||
| Variational Derivative | 变分导数 | ||
| Variational Distribution | 变分分布 | ||
| Variational Dropout | 变分暂退法 | ||
| Variational EM Algorithm | 变分EM算法 | ||
| Variational Free Energy | 变分自由能 | ||
| Variational Inference | 变分推断 | ||
| Vector | 向量 | ||
| Vector Space | 向量空间 | ||
| Vector Space Model | 向量空间模型 | VSM | |
| Vectorization | 向量化 | ||
| Version Space | 版本空间 | ||
| Virtual Adversarial Example | 虚拟对抗样本 | ||
| Virtual Adversarial Training | 虚拟对抗训练 | ||
| Visible Layer | 可见层 | ||
| Visible Variable | 可见变量 | ||
| Viterbi Algorithm | 维特比算法 | ||
| Vocabulary | 词表 | ||
| Von Neumann Architecture | 冯 · 诺伊曼架构 | ||
| Voted Perceptron | 投票感知器 | ||
| Version Control | 版本控制 |
W
| 英文术语 | 中文翻译 | 常用缩写 | 备注 |
|---|---|---|---|
| Wake Sleep | 醒眠 | ||
| Warp | 线程束 | ||
| Wasserstein Distance | Wasserstein距离 | ||
| Wasserstein GAN | Wasserstein生成对抗网络 | WGAN | |
| Weak Classifier | 弱分类器 | ||
| Weak Duality | 弱对偶性 | ||
| Weak Learner | 弱学习器 | ||
| Weakly Learnable | 弱可学习 | ||
| Weakly Supervised Learning | 弱监督学习 | ||
| Weight | 权重 | ||
| Weight Decay | 权重衰减 | ||
| Weight Normalization | 权重规范化 | ||
| Weight Scaling Inference Rule | 权重比例推断规则 | ||
| Weight Sharing | 权共享 | ||
| Weight Space Symmetry | 权重空间对称性 | ||
| Weight Vector | 权值向量 | ||
| Weighted Distance | 加权距离 | ||
| Weighted Voting | 加权投票 | ||
| Whitening | 白化 | ||
| Wide Convolution | 宽卷积 | ||
| Width | 宽度 | ||
| Winner-Take-All | 胜者通吃 | ||
| Within-Class Scatter Matrix | 类内散度矩阵 | ||
| Word Embedding | 词嵌入 | ||
| Word Sense Disambiguation | 词义消歧 | ||
| Word Vector | 词向量 | ||
| Word Vector Space Model | 单词向量空间模型 | ||
| Word-Document Matrix | 单词-文本矩阵 | ||
| Word-Topic Matrix | 单词-话题矩阵 | ||
| Working Memory | 工作记忆 | ||
| Wrapper Method | 包裹式方法 | ||
| Workflow | 工作流 |
X
Y
Z
| 英文术语 | 中文翻译 | 常用缩写 | 备注 |
|---|---|---|---|
| Z-Score Normalization | Z值规范化 | ||
| Zero Mean | 零均值 | ||
| Zero Padding | 零填充 | ||
| Zero Tensor | 零张量 | ||
| Zero-Centered | 零中心化的 | ||
| Zero-Data Learning | 零数据学习 | ||
| Zero-Shot Learning | 零试学习 | ||
| Zipf’s Law | 齐普夫定律 |
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