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Seminar Vật lý lý thuyết và Vật lý tính toán:
Tên báo cáoBayesian learning of kernels for large margin classifiers with extended Monte Carlo method
Người trình bàyTS. Hiroshi Tsukahara
Cơ quanDepartment of research planning Denso IT Laboratory, Inc.Tokyo, Japan
NgàyThứ Ba, 06-05-2008
GiờThứ năm 10g00
Địa điểmPhòng họp tầng 1, Viện Vật lý và Điện tử, 10 Đào Tấn, Thủ Lệ, Ba Đình, Hà Nội
Tóm tắtI will introduce typical problems in pattern recognition and application of learning machines for them. Then, I will introduce the concept of large margin classifiers, especially the support vector machines (SVMs) and the kernel trick. I will propose an approach to extend the usual kernel SVMs and to learn the kernel by bayesian inference. The extended Monte Carlo method is applied to estimate the posterior distribution for the bayesian inference. The effectiveness of the proposed approach is shown in specific problems and the priority of the exchange Monte Carlo method for evaluating stochastic complexity is emphasized. Another application of the present approach to the semi-supervised learning is also discussed.