This video was recorded at Machine Learning Summer School (MLSS), Chicago 2009. This tutorial covers classification approaches that utilize both labeled and unlabeled data. We will review self-training, Gaussian mixture models, co-training, multiview learning, graph-transduction and manifold regularization, transductive SVMs, and a PAC bound for semi-supervised learning. We then discuss some new development, including online semi-supervised learning, multi-manifold learning, and human semi-supervised learning.
to participate in the discussions or
if you are not already a MERLOT member.
This will delete the comment from the database. This
operation is not reversible. Are you sure you want to do it?
Report a Broken Link
Thank you for reporting a broken "Go to
Material" link in MERLOT to help us maintain a collection of
valuable learning materials.
Link Reported as Broken
Your broken link report has been sent to
the MERLOT Team. Thank you for helping MERLOT maintain a current
collection of valuable learning materials!
Link Report Failed
Your broken link report failed to be sent.
Please try reloading the page and reporting it again. Thank you!
Sorry for the trouble.
If you feel this material is inappropriate for the MERLOT
Collection, please click SEND REPORT, and the MERLOT Team will
investigate. Thank you!
Material Reported as
Your inappropriate material report has
been sent to the MERLOT Team. Thank you for helping MERLOT maintain
a valuable collection of learning materials.
Material Report Failed
Your inappropriate material report failed
to be sent. Please try reloading the page and reporting it again.
Thank you! Sorry for the trouble.
Comment Reported as
Your inappropriate comment report has been
sent to the MERLOT Team. Thank you for helping MERLOT maintain a
valuable collection of learning materials.
You are being taken to the material on
another site. This will open a new window.
Rate this Material
You just viewedSemi-Supervised Learning.
Please take a moment to rate this material.
Search by ISBN?
It looks like you have entered an ISBN number. Would you like to search using what you have
entered as an ISBN number?
Searching for Members?
You entered an email address. Would you like to search for members? Click Yes to continue. If no, materials will be displayed first. You can refine your search with the options on the left of the results page.