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NIPS
2004
15 years 3 months ago
Semi-supervised Learning by Entropy Minimization
We consider the semi-supervised learning problem, where a decision rule is to be learned from labeled and unlabeled data. In this framework, we motivate minimum entropy regulariza...
Yves Grandvalet, Yoshua Bengio
ECML
2004
Springer
15 years 7 months ago
Exploiting Unlabeled Data in Content-Based Image Retrieval
Abstract. In this paper, the Ssair (Semi-Supervised Active Image Retrieval) approach, which attempts to exploit unlabeled data to improve the performance of content-based image ret...
Zhi-Hua Zhou, Ke-Jia Chen, Yuan Jiang
TCS
2002
15 years 1 months ago
Unsupervised learning in neural computation
In this article, we consider unsupervised learning from the point of view of applying neural computation on signal and data analysis problems. The article is an introductory surve...
Erkki Oja
PAMI
2011
14 years 8 months ago
Greedy Learning of Binary Latent Trees
—Inferring latent structures from observations helps to model and possibly also understand underlying data generating processes. A rich class of latent structures are the latent ...
Stefan Harmeling, Christopher K. I. Williams
AAAI
2007
15 years 4 months ago
Learning by Combining Observations and User Edits
We introduce a new collaborative machine learning paradigm in which the user directs a learning algorithm by manually editing the automatically induced model. We identify a generi...
Vittorio Castelli, Lawrence D. Bergman, Daniel Obl...