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JMLR
2012
13 years 9 months ago
Structured Output Learning with High Order Loss Functions
Often when modeling structured domains, it is desirable to leverage information that is not naturally expressed as simply a label. Examples include knowledge about the evaluation ...
Daniel Tarlow, Richard S. Zemel
JMLR
2012
13 years 9 months ago
Online Incremental Feature Learning with Denoising Autoencoders
While determining model complexity is an important problem in machine learning, many feature learning algorithms rely on cross-validation to choose an optimal number of features, ...
Guanyu Zhou, Kihyuk Sohn, Honglak Lee
ALT
2009
Springer
16 years 4 months ago
Iterative Learning from Texts and Counterexamples Using Additional Information
Abstract. A variant of iterative learning in the limit (cf. [LZ96]) is studied when a learner gets negative examples refuting conjectures containing data in excess of the target la...
Sanjay Jain, Efim B. Kinber
HRI
2006
ACM
16 years 1 months ago
Structural descriptions in human-assisted robot visual learning
The paper presents an approach to using structural descriptions, obtained through a human-robot tutoring dialogue, as labels for the visual object models a robot learns. The paper...
Geert-Jan M. Kruijff, John D. Kelleher, Gregor Ber...
MM
2005
ACM
123views Multimedia» more  MM 2005»
16 years 22 days ago
How speech/text alignment benefits web-based learning
This demonstration presents an integrated web-based synchronized scenario for many-to-one cross-media correlations between speech (an EFL, English as Foreign Language, lecture wit...
Sheng-Wei Li, Hao-Tung Lin, Herng-Yow Chen