Abstract. The tutorial starts with an overview of the concepts of VC dimension and structural risk minimization. We then describe linear Support Vector Machines (SVMs) for separable and non-separable data, working through a non-trivial example in de
Two experiments investigated the effectiveness of computer-assisted prosody training, its generalization to novel sentences and segmental accuracy, and the relationship between prosodic and lexical information in long-term memory. Experiment 1, usin
This paper introduces a novel measure-theoreticlearning theory to analyze generalization behaviors of practical interest. The proposed learningtheory has the following abilities: 1) to utilizethe qualities of each learned representation onthe path fr
With a direct analysis of neural networks, this paper presents a mathematically tight
generalization theory to partially address an open problem regarding the generalization
of deep learning. Unlike previous bound-based theory, our main theory is q
混合样本ERM算法的推广性能，邹斌，李落清，The generalization performance is the main purpose of machine learning theoretical research. The previous main bounds describing the generalization ability of ERM algorithm are b
numerical observers比较好的一篇文献，比较好的一篇文献Figure 2(left)shows the calculated A, by the different generalize better when the test images are reconstructed in a
methods. These results suggest that both CSVM and CHO can
different way from that of training ima
