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...
Categories of learning process are proposed and described, as follows: motor skills, verbal information, intellectual skills, cognitive strategies, attitudes. Research evidence on school learning suggests that generalizations about critical learning conditions and outcomes can be validly made within these ca...
learning domainstransformative learning theoryTransformative learning theory is applied in a variety of fields, including archaeology, religious studies, health care, the physical sciences, environmental studies, and natural resource management. Given the breadth of the theory’s application, it needs to ...
A theory of learning from different domains 152 Mach Learn (2010) 79: 151175 We address the rst question by bounding a classiers target error in terms of its source error and the divergence between the two domains. We give a classier-induced divergence measure that can be estimated from nit...
In many scientific fields, sparseness and indirectness of empirical evidence pose fundamental challenges to theory development. Theories of the evolution o
In this lesson, we will discuss how the psychomotor, cognitive, and affective domains of learning apply to physical education. We will also...
A theory of learning from different domains Discriminative learning methods for classification perform well when training and test data are drawn from the same distribution. Often, however, we have p... S Ben-David,J Blitzer,K Crammer,... - 《Machine Learning》 被引量: 784发表: 2010年 A ...
Machine learning systems addressing this problem generally use an incremental learning, on-line paradigm. An off-line, meta-learning approach to the identification of hidden context is presented. This approach uses an existing batch learner and the process of contextual clustering to identify stable ...
Leading Teacher Program Themes & Domains Themes The learning experiences reflect the themes of leadership, diversity and technology and are infused...
This paper discusses the role of authenticity and authenticity claims in computer assisted language learning (CALL). It considers authenticity as the result of a social negotiation process rather than an innate feature of a text, object, person, or activity. From this basis, it argues that authen...