Seminars

Year 2010

• Wednesday 16th June 2010 at 10:00: Issues about Embedding Prior Information onto Learning Machines - Examples on Neural Network Models - Prof. Baogang Hu of the National Laboratory of Pattern Recognition, Institute of Automation,from Chinese Academy of Sciences.
  

  Abstract:This talk will discuss the maximum uses of prior information in studies of machine learning, and their related issues. When we recognize a critical role of prior information in modeling, up to now we still miss a systematic investigation into the subject. For example, in apart from Bayesian framework or knowledge-based inference, do we need other generic approaches which are able to integrate any type of prior information? For addressing this issue, we propose a generalized constraint modeling approach. Using this approach, one can improve neural networks through maximum uses of prior information. Examples are given on regression and dynamic process problems. The main objective of this talk is to highlight the issues for a systematic study on the subject from a mathematic challenge, rather than from specific applications.

  
  
  

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