Semantic Scholar Open Access 1993 3647 sitasi

Hierarchical Mixtures of Experts and the EM Algorithm

M. I. Jordan R. Jacobs

Lihat Sumber DOI

Abstrak

We present a tree-structured architecture for supervised learning. The statistical model underlying the architecture is a hierarchical mixture model in which both the mixture coefficients and the mixture components are generalized linear models (GLIM's). Learning is treated as a maximum likelihood problem; in particular, we present an Expectation-Maximization (EM) algorithm for adjusting the parameters of the architecture. We also develop an on-line learning algorithm in which the parameters are updated incrementally. Comparative simulation results are presented in the robot dynamics domain.

Topik & Kata Kunci

Computer Science Mathematics

Penulis (2)

M. I. Jordan

R. Jacobs

Format Sitasi

APA MLA BibTeX

Jordan, M.I., Jacobs, R. (1993). Hierarchical Mixtures of Experts and the EM Algorithm. https://doi.org/10.1109/IJCNN.1993.716791

Akses Cepat

Lihat di Sumber doi.org/10.1109/IJCNN.1993.716791

Informasi Jurnal

Tahun Terbit: 1993
Bahasa: en
Total Sitasi: 3647×
Sumber Database: Semantic Scholar
DOI: 10.1109/IJCNN.1993.716791
Akses: Open Access ✓