5. A learning bound combining source and target training data现在考虑这样的学习模式: 训练集为 S=(ST,SS)S=(ST,SS), 其中 STST 为βmβm 个从分布 DTDT 中采样的实例, SSSS 为(1−β)m(1−β)m 个从分布 DSDS 中独立采样的实例. 学习的目标是寻找一个 hh 以最小化 ϵT(h)ϵT(h...
Ben-David S, Blitzer J, Crammer K, Kulesza A, Pereira F, Vaughan JW (2010) A theory of learning from different domains. Mach Learn 79(1–2):151–175 MathSciNetBen-David S, Blitzer J, Crammer K, Kulesza A, Pereira F, Vaughan J W. A theory of learning from different domains. ...
The resulting bound generalizes the previously studied cases and is always at least as tight as a bound which considers minimizing only the target error or an equal weighting of source and target errors. 展开 关键词: Domain adaptation Learning theory Sample-selection bias Transfer learning ...
标题 A theory of learning from different domains 作者 Ben-david, Shai; Blitzer, John; Crammer, Koby; Kulesza, Alex; Pereira, Fernando; Vaughan, Jennifer Wortman 页 151-175 出版年份 2010 出版日期 May 2010 出版商 Springer Nature B.V. ISSN 08856125 e-ISSN 15730565 来源类型 学术期刊 出版物语...
Ben-David, S., Blitzer, J., Crammer, K., Kulesza, A., Pereira, F., and Vaughan, J. W. A theory of learning from different domains. Machine Learning, 79(1-2):151–175, 2010. A Brief Introduction of Domain Adaptation(可以直接看大佬的博客) ...
Ben-David, S.et al.A theory of learning from different domains.Mach. Learn.79, 151–175 (2010). ArticleMathSciNetGoogle Scholar Dong, T.et al.Generative adversarial network-based transfer reinforcement learning for routing with prior knowledge.IEEE Trans. Network Service Manag.(2021). ...
A theory of learning from different domains [ML2010] Unsupervised DA Adversarial Methods Conference Implicit Class-Conditioned Domain Alignment for Unsupervised Domain Adaptation [ICML2020] [Pytorch] Adversarial-Learned Loss for Domain Adaptation [AAAI2020] Adversarial Domain Adaptation with Domain Mixup [...
A complete summary of the 15 most influential learning theories. Includes Vygotsky, Piaget, Bloom, Gagne, Maslow, Bruner, Kolb and many more.
Practice tells you that things are good or bad; theory tells you why. Not being qualified to solve a problem is no reason not to solve it. If you don't understand a system you're using, you don't control it. If nobody understands the system, the system is in control. Embedded Rule...
A reliability-based consensus model and regret theory-based selection process for linguistic hesitant-Z multi-attribute group decision making. Expert Syst. Appl. 2023, 228, 120431. [Google Scholar] [CrossRef] Zhang, D.A.F.; Li, Y.L.; Li, Y.Q.; Shen, Z.F. Service failure risk ...