人工智能專(zhuān)業(yè)術(shù)語(yǔ)Artificial-Intelligence-Terminology I
| 英文/縮寫(xiě) | 漢語(yǔ) |
|---|---|
| ICML | 國(guó)際機(jī)器學(xué)習(xí)會(huì)議 |
| Identity matrix | 單位矩陣 |
| Image restoration | 圖像復(fù)原 |
| Improved iterative scaling/IIS | 改進(jìn)的迭代尺度法 |
| Incremental learning | 增量學(xué)習(xí) |
| Independent and identically distributed/i.i.d. | 獨(dú)立同分布 |
| Independent Component Analysis/ICA | 獨(dú)立成分分析 |
| Independent subspace analysis | 獨(dú)立子空間分析 |
| Indicator function | 指示函數(shù) |
| Individual learner | 個(gè)體學(xué)習(xí)器 |
| Induction | 歸納 |
| Inductive bias | 歸納偏好 |
| Inductive learning | 歸納學(xué)習(xí) |
| Inductive Logic Programming/ILP | 歸納邏輯程序設(shè)計(jì) |
| Inequality constraint | 不等式約束 |
| Information entropy | 信息熵 |
| Information gain | 信息增益 |
| Input layer | 輸入層 |
| Insensitive loss | 不敏感損失 |
| Inter-cluster similarity | 簇間相似度 |
| International Conference for Machine Learning/ICML | 國(guó)際機(jī)器學(xué)習(xí)大會(huì) |
| Intra-cluster similarity | 簇內(nèi)相似度 |
| Intrinsic value | 固有值 |
| Invariance | 不變性 |
| Invert | 求逆 |
| Isometric Mapping/Isomap | 等度量映射 |
| Isotonic regression | 等分回歸 |
| Iterative Dichotomiser | 迭代二分器 |
人工智能專(zhuān)業(yè)術(shù)語(yǔ)
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