ICML
2003
IEEE
15 years 10 days ago
2003
IEEE
This paper analyzes the performance of semisupervised learning of mixture models. We show that unlabeled data can lead to an increase in classification error even in situations wh...
ICML
2005
IEEE
15 years 10 days ago
2005
IEEE
Due to its occurrence in engineering domains and implications for natural learning, the problem of utilizing unlabeled data is attracting increasing attention in machine learning....
ICML
2005
IEEE
15 years 10 days ago
2005
IEEE
We introduce a Bayesian model, BayesANIL, that is capable of estimating uncertainties associated with the labeling process. Given a labeled or partially labeled training corpus of...
ICML
2007
IEEE
15 years 10 days ago
2007
IEEE
We consider a setting for discriminative semisupervised learning where unlabeled data are used with a generative model to learn effective feature representations for discriminativ...
ICML
2007
IEEE
15 years 10 days ago
2007
IEEE
We present a new machine learning framework called "self-taught learning" for using unlabeled data in supervised classification tasks. We do not assume that the unlabele...
ICML
2009
IEEE
15 years 10 days ago
2009
IEEE
This work proposes a learning method for deep architectures that takes advantage of sequential data, in particular from the temporal coherence that naturally exists in unlabeled v...
ICML
2009
IEEE
15 years 10 days ago
2009
IEEE
Semi-Supervised Support Vector Machines (S3VMs) typically directly estimate the label assignments for the unlabeled instances. This is often inefficient even with recent advances ...
ICCV
2003
IEEE
15 years 1 months ago
2003
IEEE
One significant challenge in the construction of visual detection systems is the acquisition of sufficient labeled data. This paper describes a new technique for training visual d...
ICCV
2007
IEEE
15 years 1 months ago
2007
IEEE
Closing the semantic gap in content based image retrieval (CBIR) basically requires the knowledge of the user's intention which is usually translated into a sequence of quest...
CVPR
2008
IEEE
15 years 1 months ago
2008
IEEE
To learn a new visual category from few examples, prior knowledge from unlabeled data as well as previous related categories may be useful. We develop a new method for transfer le...