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JMLR
2012
13 years 6 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
184
Voted
JMLR
2012
13 years 6 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 1 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
15 years 10 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...
109
Voted
MM
2005
ACM
123views Multimedia» more  MM 2005»
15 years 9 months 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