(1)Data-Free Learning of Student Networks(ICCV2019) GAN + KD 解析:【已开源】华为诺亚方舟实验室提出无需数据网络压缩技术 (2)Dreaming to Distill: Data-free Knowledge Transfer via DeepInversion (CVPR2020) BNS + 图像方差及L2-Norm的惩罚项 + JS(输出分布相似性惩罚项,增强数据多样性) (3)Large-Sca...
Inception ( I ) BN-Stats(BNS) BNS + I 5.1 Inception scheme 给定一个随机的目标类别,然后最大化该类别的score,loss定义如下: scale是超参 5.2 BN-Stats(BNS) teacher中BN统计量是含有训练样本信息的, 希望生成样本的统计量也与原BN统计量相似; 5.3 其它:与图片先验相关的loss 通常图片是比较平滑的。每次...
we replace the BNS in the quantized model with the fixed batch normalization statistics (FBNS) as described in Sect.4.2. So far, the quantized model has inherited the information contained in BNS and a part of latent knowledge from the parameters of the pre-trained model. In the fine-tuning...
Maximum likelihood method for estimating parameters of Bayesian networks (BNs) is efficient and accurate for large samples. However, the method suffers from overfitting when the sample size is small. Bayesian methods, which are effective to avoid overfitting, present difficulties for determining optimal...
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A technique converts a stream of virtual volume block numbers (vvbns) into a hybrid virtual volume (vvol) file system containing both physical volume block numbers (pvbns) and vvbns. The stream of vvbns is illustratively embodied as a file system data stream of a vvol that is transferred...
Maximum likelihood method for estimating parameters of Bayesian networks (BNs) is efficient and accurate for large samples. However, the method suffers from overfitting when the sample size is small. Bayesian methods, which are effective to avoid overfitting, present difficulties for determining optimal...