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» Learning to Identify Unexpected Instances in the Test Set
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EMNLP
2010
13 years 5 months ago
Improved Fully Unsupervised Parsing with Zoomed Learning
We introduce a novel training algorithm for unsupervised grammar induction, called Zoomed Learning. Given a training set T and a test set S, the goal of our algorithm is to identi...
Roi Reichart, Ari Rappoport
CVPR
2007
IEEE
14 years 9 months ago
An Exemplar Model for Learning Object Classes
We introduce an exemplar model that can learn and generate a region of interest around class instances in a training set, given only a set of images containing the visual class. T...
Ondrej Chum, Andrew Zisserman
ICIAR
2005
Springer
14 years 26 days ago
Machine-Learning-Based Image Categorization
In this paper, a novel and efficient automatic image categorization system is proposed. This system integrates the MIL-based and global-featurebased SVMs for categorization. The IP...
Yutao Han, Xiaojun Qi
CVPR
2008
IEEE
14 years 1 months ago
Manifold-Manifold Distance with application to face recognition based on image set
In this paper, we address the problem of classifying image sets, each of which contains images belonging to the same class but covering large variations in, for instance, viewpoin...
Ruiping Wang, Shiguang Shan, Xilin Chen, Wen Gao
KDD
2009
ACM
180views Data Mining» more  KDD 2009»
14 years 8 months ago
Using graph-based metrics with empirical risk minimization to speed up active learning on networked data
Active and semi-supervised learning are important techniques when labeled data are scarce. Recently a method was suggested for combining active learning with a semi-supervised lea...
Sofus A. Macskassy