University of Birmingham > Talks@bham > Artificial Intelligence and Natural Computation seminars > Research on Semi-Supervised Support Vector Machine

  Browse A-Z

Log in

System Admin (disabled)details Birmingham usersdetails No account?details

Information on

Subscribing to talksdetails Finding a talkdetails Adding a talkdetails Disseminating talksdetails Help and Documentationdetails

Research on Semi-Supervised Support Vector Machine

Add to your list(s) Download to your calendar using vCal

If you have a question about this talk, please contact Leandro Minku.

Host: Dr. Shan He

Exploiting unlabelled data to help improve the performance is fundamental to machine learning research. Semi-Supervised learning is one major branch in this direction, and Semi-Supervised SVM (S3VM) is one of the most basic, popular Semi-Supervised learning paradigms. Many researchers have studied S3VM since S3VM was proposed. However, the scalability, the efficiency, the safeness, and the learning cost of S3V Ms have not been well addressed. In this paper, I will present some of our recent progress on these issues.

This talk is part of the Artificial Intelligence and Natural Computation seminars series.

Tell a friend about this talk:

This talk is included in these lists:

Note that ex-directory lists are not shown.

Other lists

Medical Imaging Research Seminars School of Mathematics Events Metamaterials Research Group Seminars

Other talks

Sensing and metrology activities at NPL, India Perfect matchings in random sparsifications of Dirac hypergraphs TBC Geometry of alternating projections in metric spaces with bounded curvature Hodge Theory: Connecting Algebra and Analysis Quantum simulations using ultra cold ytterbium
 

Talks@bham, University of Birmingham. Contact Us | Help and Documentation | Privacy and Publicity.
talks@bham is based on talks.cam from the University of Cambridge.