13 - 3 - Deterministic Noise (14-07)
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14 - 4 - General Regularizers (13-28)
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14 - 2 - Weight Decay Regularization (24-08)
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13 核主元分析
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8 - 3 - Algorithmic Error Measure (13-46)
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8 - 1 - Noise and Probabilistic Target (17-01)
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16 - 1 - Occam-'s Razor (10-08)
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41 Boosting1
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7 - 2 - VC Dimension of Perceptrons (13-27)
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29 谱聚类1
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15 Wishart 分布
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10 - 1 - Logistic Regression Problem (14-33)
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17 概率PCA
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15 主坐标分析
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7 - 4 - Interpreting VC Dimension (17-13)
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25 spectral clustering
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4 - 1 - Learning is Impossible- (13-32)
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6 条件期望
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31 Computational Methods1
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32 随机投影
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37 Naive Bayes方法
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04 高斯分布
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02 随机变量1
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28 Fisher判别分析
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01 概率基础
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8 多元高斯分布及应用
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13 - 2 - The Role of Noise and Data Size (13-36)
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03 随机变量2
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11 正定核性质
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12 正定核应用
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10 - 4 - Gradient Descent (19-18)(1)
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14-PCL教程-基础应用-在自己的项目中使用PCL
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5 - 1 - Recap and Preview (13-44)
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7 多项式分布
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38 Support Vector Machines1
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杨照 《史记百讲》【完结版】
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06 连续分布
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16 - 2 - Sampling Bias (11-50)
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3 - 4 - Learning with Different Input Space (14-13)
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39 Support Vector Machines2