750 search results - page 71 / 150 » Learning SVMs from Sloppily Labeled Data |
139
click to vote
EMMCVPR
2011
Springer
14 years 4 months ago
2011
Springer
The challenge of recovering the topology of massive neuronal circuits can potentially be met by high throughput Electron Microscopy (EM) imagery. Segmenting a 3-dimensional stack o...
175
click to vote
ACL
2009
15 years 2 months ago
2009
Creating labeled training data for relation extraction is expensive. In this paper, we study relation extraction in a special weakly-supervised setting when we have only a few see...
159
click to vote
JMLR
2010
14 years 11 months ago
2010
In this paper we learn a dissimilarity measure for categorical data, for effective classification of the data points. Each categorical feature (with values taken from a finite set...
149
click to vote
DASFAA
2004
IEEE
15 years 8 months ago
2004
IEEE
Text classification using a small labeled set and a large unlabeled data is seen as a promising technique to reduce the labor-intensive and time consuming effort of labeling traini...
161
click to vote
DMIN
2007
15 years 5 months ago
2007
— One way to handle data mining problems where class prior probabilities and/or misclassification costs between classes are highly unequal is to resample the data until a new, d...