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机译:Rademacher辍学:通过优化泛化差距来实现深神经网络的自适应辍学
Natl Univ Def Technol Coll Comp State Key Lab High Performance Comp HPCL Changsha Hunan Peoples R China;
Natl Univ Def Technol Coll Comp State Key Lab High Performance Comp HPCL Changsha Hunan Peoples R China;
Natl Univ Def Technol Coll Liberal Arts & Sci Changsha Hunan Peoples R China;
Natl Univ Def Technol Coll Liberal Arts & Sci Changsha Hunan Peoples R China;
Natl Univ Def Technol Coll Comp State Key Lab High Performance Comp HPCL Changsha Hunan Peoples R China;
Natl Univ Def Technol Coll Comp State Key Lab High Performance Comp HPCL Changsha Hunan Peoples R China;
Overfitting; Dropout; Rademacher complexity; Generalization gap; Deep neural network;
机译:Rademacher辍学:通过优化泛化差距来进行深度神经网络的自适应辍学
机译:自适应稀疏辍学:在深神经网络中学习确定性和不确定性
机译:基于优化卷积神经网络 - 自适应辍学深度计算的医学图像分割算法
机译:受控辍学:用于提高深度神经网络训练速度的另一种辍学方法
机译:用于训练深度神经网络的自适应辍学。
机译:神经网络中的辍学模拟深脑刺激对记忆的矛盾作用
机译:深度神经网络的辍学Rademacher复杂性