5、 Max-Norm Regularization 虽然单独使用 dropout 就可以使得模型获得良好表现,不过,如果搭配Max-Norm 食用的话,那么效果更佳。 对于每一个神经元 Max-Norm Regularization 的目的在于限制输入链接权重的大小,使得||w||_2 \ll r,其中 r 是Max-Norm 可调节超参数,||.||_2是L2范数。在每一个 training step...
回到顶部 Max-Norm Regularization 对于每个节点,max-norm regularization 会对权重w进行限制‖w‖2≤r: (1)w←wr‖w‖2 实例代码: View Code
内容提示: Practical Large-Scale Optimizationfor Max-Norm RegularizationJason LeeInstitute of Computational and Mathematical EngineeringStanford Universityemail: jl115@yahoo.comBenjamin RechtDepartment of Computer SciencesUniversity of Wisconsin-Madisonemail: brecht@cs.wisc.eduRuslan SalakhutdinovBrain and Cognitive...
Practical Large-Scale Optimization for Max-Norm Regularization.pdf,Practical Large-Scale Optimization for Max-Norm Regularization Jason Lee Benjamin Recht Institute of Computational and Mathematical Engineering Department of Computer Sciences Stanford Un
Online optimization for max-norm regularization. In Advances in Neural Information Processing Systems, pages 1718-1726, 2014. → pages 40Shen Jie; Xu Huan; and Li Ping.Online optimization for max-norm regularization.Electronic Proceedings of the Neural Information Processing Systems Conference.2014.1718...
Although the max-norm can be computed in polynomial time, there are currently no practical algorithms for solving large-scale optimization problems that incorporate the max-norm. The present work uses a factorization technique of Burer and Monteiro [2] to devise scalable first-order algorithms for ...
示例1: test_maxnorm ▲点赞 5▼ # 需要导入模块: from keras import constraints [as 别名]# 或者: from keras.constraints importmaxnorm[as 别名]deftest_maxnorm(self):fromkeras.constraintsimportmaxnormforminself.some_values: norm_instance =maxnorm(m) ...
if normalize: #是否进行normalization layers.append(nn.BatchNorm1d(out_feat, 0.8)) #如...
MPSNNRegularizationType MPSNNReshape MPSNNReshapeGradient MPSNNReshapeGradientNode MPSNNReshapeNode MPSNNResizeBilinear MPSNNScaleNode MPSNNSlice MPSNNStateNode MPSNNSubtractionGradientNode MPSNNSubtractionNode MPSNNTrainingStyle MPSNNUnaryReductionNode MPSOffset MPSOrigin MPSPurgeableState MPSRayDataType MPSRay...
Parameters --- parameters : list of theano variables Parameters to apply the regularization. l1_coefficient : float Weighting for L1 regularization contribution. l2_coefficient : float Weighting for L2 regularization contribution. Returns --- theano expression The appropriate regularized parameters as a ...