Talker: Jen-Tzung Chien (NCTU)
Title: Bayesian nonparametric information processing
Abstract: This talk surveys a series of Bayesian nonparametric (BNP)
approaches to statistical temporal modeling and their inference
procedures which are applied to build information systems including
speech recognition, document classification, document summarization
and document retrieval. Our goal is to design a flexible, scalable,
hierarchical and robust topic models to meet heterogeneous and
nonstationary environments in the era of big data. Two recent works
on BNP learning are introduced. One is the hierarchical
Pitman-Yor-Dirichlet process for language modeling. The other is the
hierarchical theme and topic modeling for document modeling.
- slides
- video