| Saddle point |
鞍點(diǎn) |
| Saddle-free Newton method |
無(wú)鞍牛頓法 |
| Sample space |
樣本空間 |
| Sampling |
采樣 |
| Score function |
評(píng)分函數(shù) |
| Second derivative |
二階導(dǎo)數(shù) |
| Second-order method |
二階方法 |
| Self-contrastive estimation |
自對(duì)比估計(jì) |
| Self-Driving |
自動(dòng)駕駛 |
| Self-Organizing Map/SOM |
自組織映射 |
| Semantic hashing |
語(yǔ)義哈希 |
| Semantic similarity |
語(yǔ)義相似度 |
| Semi-Definite Programming |
半正定規(guī)劃 |
| Semi-naive Bayes classifiers |
半樸素貝葉斯分類器 |
| Semi-restricted Boltzmann Machine |
半受限波爾茲曼機(jī) |
| Semi-Supervised Learning |
半監(jiān)督學(xué)習(xí) |
| semi-Supervised Support Vector Machine |
半監(jiān)督支持向量機(jī) |
| Sentiment analysis |
情感分析 |
| Separating hyperplane |
分離超平面 |
| Shannon entropy |
香農(nóng)熵 |
| Sigmoid function |
Sigmoid 函數(shù) |
| Similarity measure |
相似度度量 |
| Simulated annealing |
模擬退火 |
| Simultaneous localization and mapping/SLAM |
同步定位與地圖構(gòu)建 |
| Singular value |
奇異值 |
| Singular Value Decomposition |
奇異值分解 |
| Slack variables |
松弛變量 |
| Slowness principle |
慢性原則 |
| Smoothing |
平滑 |
| Smoothness prior |
平滑先驗(yàn) |
| Soft margin |
軟間隔 |
| Soft margin maximization |
軟間隔最大化 |
| Soft voting |
軟投票 |
| Sparse activation |
稀疏激活 |
| Sparse coding |
稀疏編碼 |
| Sparse connectivity |
稀疏連接 |
| Sparse initialization |
稀疏初始化 |
| Sparse representation |
稀疏表征 |
| Sparsity |
稀疏性 |
| Specialization |
特化 |
| Spectral Clustering |
譜聚類 |
| Spectral radius |
譜半徑 |
| Speech Recognition |
語(yǔ)音識(shí)別 |
| Spiking Neural Nets |
脈沖神經(jīng)網(wǎng)絡(luò) |
| Splitting variable |
切分變量 |
| Squashing function |
擠壓函數(shù) |
| Stability-plasticity dilemma |
可塑性-穩(wěn)定性困境 |
| Stacked Deconvolutional Network/SDN |
堆疊解卷積網(wǎng)絡(luò) |
| Standard deviation |
標(biāo)準(zhǔn)差 |
| Stationary distribution |
穩(wěn)態(tài)分布 |
| Stationary point |
駐點(diǎn) |
| Statistical learning |
統(tǒng)計(jì)學(xué)習(xí) |
| Status feature function |
狀態(tài)特征函數(shù) |
| Stochastic gradient descent |
隨機(jī)梯度下降 |
| Stochastic Matrix |
隨機(jī)矩陣 |
| Stochastic maximum likelihood |
隨機(jī)最大似然 |
| Stochastic Neighbor Embedding |
隨機(jī)近鄰嵌入 |
| Stratified sampling |
分層采樣 |
| Structural risk |
結(jié)構(gòu)風(fēng)險(xiǎn) |
| Structural risk minimization/SRM |
結(jié)構(gòu)風(fēng)險(xiǎn)最小化 |
| Structured variational inference |
結(jié)構(gòu)化變分推斷 |
| Subspace |
子空間 |
| Supervised learning |
監(jiān)督學(xué)習(xí)／有導(dǎo)師學(xué)習(xí) |
| support vector expansion |
支持向量展式 |
| Support Vector Machine/SVM |
支持向量機(jī) |
| Surrogat loss |
替代損失 |
| Surrogate function |
替代函數(shù) |
| Symbolic learning |
符號(hào)學(xué)習(xí) |
| Symbolism |
符號(hào)主義 |
| Synset |
同義詞集 |
| Synthetic feature |
合成特征 |
