深度学习的迁移模型（46页）.pdf

1、深度学习的迁移模型杨强香港香港科技科技大学，大学，新明新明工程学讲座工程学讲座教授教授计算机计算机与工程系与工程系主任主任,大大数据研究所主任数据研究所主任AlphaGo 还不会做什么？举一反三19x1921X21深度学习的迁移模型深度学习的迁移模型迁移学习 Transfer Learning迁移学习 下一个热点：迁移学习 Transfer Learning迁移学习 Transfer Learning迁移学习的优点 1:小数据迁移学习的优点 2:可靠性ModelDomain1Domain2Domain3Domain4迁移学习的优点 3:个性化迁移学习的难点迁移学习本质:找出不变量Driving

2、 in Mainland ChinaDriving in Hong Kong,ChinaOne Knowledge,Two Domains Yann LeCun:机器学习的热力学模型?（百度百科）热力学主要是从能量转化的观点来研究物质的热性质，它提示了能量从一种形式转换为另一种形式时遵从的宏观规律，总结了物质的宏观现象而得到的热学理论。迁移学习 Transfer Learning深度学习迁移学习:多层次的特征学习 Bengio,Yoshua,Aaron Courville,and Pascal Vincent.Representation learning:A review and new p

3、erspectives.IEEE transactions on pattern analysis and machine intelligence 35.8(2013):1798-1828.深度学习的迁移模型:定量分析inputoutputinputoutputdomain distance lossshared weightsTCA:Transfer Component Analysis:Pan,Sinno Jialin,Ivor W.Tsang,James T.Kwok,and Qiang Yang.Domain adaptation via transfer component ana

4、lysis.IEEE Transactions on Neural Networks 22,no.2(2011):199-210.GFK:Geodesic Flow Kernel:Gong,Boqing,Yuan Shi,Fei Sha,and Kristen Grauman.Geodesic flow kernel for unsupervised domain adaptation.In Computer Vision and Pattern Recognition(CVPR),2012 IEEE Conference on,pp.2066-2073.IEEE,2012.DLID:Deep

5、 Learning for domain adaptation by Interpolating between Domains:Chopra,Sumit,Suhrid Balakrishnan,and Raghuraman Gopalan.Dlid:Deep learning for domain adaptation by interpolating between domains.ICML workshop on challenges in representation learning.Vol.2.2013.DDC:Deep Domain Confusion:Tzeng,Eric,Ju

6、dy Hoffman,Ning Zhang,Kate Saenko,and Trevor Darrell.Deep domain confusion:Maximizing for domain invariance.arXiv preprint arXiv:1412.3474(2014).DAN:Deep Adaptation Networks:Long,Mingsheng,Yue Cao,Jianmin Wang,and Michael Jordan.Learning transferable features with deep adaptation networks.In Interna