对于OFFICE域,我们使用来自caffe包的预训练的AlexNet 模型(Jia et al., 2014)。适应架构与Tzeng et al.(2014)(A 2-layer domain classifier (x→1024→1024→2) is attached to the 256-dimensional bottleneck of fc7)相同 对于域自适应组件,我们使用了三个全连接层(x→1024→1024→2)(除了MNIST,其我们使...
JournalofMachineLearningResearch17(2016)1-35Submitted5/15;Published4/16Domain-AdversarialTrainingofNeuralNetworksYaroslavGaninganin@skoltech.ruE..
DomainAdversarial Training of Neural Networks 下载积分: 1000 内容提示: Chapter 10Domain-Adversarial Training of NeuralNetworksYaroslav Ganin, Evgeniya Ustinova, Hana Ajakan, Pascal Germain,Hugo Larochelle, François Laviolette, Mario Marchandand Victor LempitskyAbstract Weintroducearepresentationlearning...
(2016) Domain-adversarial training of neural networks. The Journal of Machine Learning Research 17(1), 2096-2030Ganin, Y., Ustinova, E., Ajakan, H., Germain, P., Larochelle, H., Laviolette, F., Marchand, M., Lempitsky, V.: Domain-adversarial training of neural networks. Journal of...
内容提示: Journal of Machine Learning Research 17 (2016) 1-35 Submitted 5/15; Published 4/16Domain-Adversarial Training of Neural NetworksYaroslav Ganin ganin@skoltech.ruEvgeniya Ustinova evgeniya.ustinova@skoltech.ruSkolkovo Institute of Science and Technology (Skoltech)Skolkovo, Moscow Region, ...
Quantization and Training of Neural Networks for Efficient Integer-Arithmetic-Only Inference 摘要 作者提出了一种只使用整数运算的quantization方式,比起float point运算效率更高。同时提出了一种相应的训练方式来保证quantization之后的准确率。这篇文章的方法提升了accuracy和on-device latency之间的trade off,并且可...
domain-adversarial training of neural networks 神经网络的领域对抗训练 重点词汇释义 neural神经的; 背的，背侧的 networks网( network的名词复数 ); 网络; 网状物; 广播网
论文地址:Domain-Adversarial Training of Neural Networks Adversarial Discriminative Domain Adaptation 代码地址:pytorch-domain-adaptation 自2018年以来,领域自适应发展地非常迅速,这很大一部分得益于下游应用的广泛需要。深度学习作为一门数据驱动的科学,在任何领域都需要大量的标注数据来训练。暂时还没有能力使得无监督或...
Adversarial training of neural networks Methods, systems, and apparatus, including computer programs encoded on computer storage media, for adversarial training of a neural network. One of the methods includes obtaining a plurality of training inputs; and training the neural n... C Szegedy,I Goodfe...
Domain-Adversarial Training of Neural Networks: We introduce a new representation learning approach for domain adaptation, in which data at training and test ti