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DIS
2010
Springer
14 years 8 months ago
Speeding Up and Boosting Diverse Density Learning
Abstract. In multi-instance learning, each example is described by a bag of instances instead of a single feature vector. In this paper, we revisit the idea of performing multi-ins...
James R. Foulds, Eibe Frank
EMNLP
2006
14 years 11 months ago
Semantic Role Labeling via Instance-Based Learning
This paper demonstrates two methods to improve the performance of instancebased learning (IBL) algorithms for the problem of Semantic Role Labeling (SRL). Two IBL algorithms are u...
Chi-san Althon Lin, Tony C. Smith
IJCNN
2008
IEEE
15 years 4 months ago
Kernel methods for fMRI pattern prediction
Abstract— In this paper, we present an effective computational approach for learning patterns of brain activity from the fMRI data. The procedure involved correcting motion artif...
Yizhao Ni, Carlton Chu, Craig J. Saunders, John As...
COLT
2008
Springer
14 years 11 months ago
Does Unlabeled Data Provably Help? Worst-case Analysis of the Sample Complexity of Semi-Supervised Learning
We study the potential benefits to classification prediction that arise from having access to unlabeled samples. We compare learning in the semi-supervised model to the standard, ...
Shai Ben-David, Tyler Lu, Dávid Pál
FUIN
2006
107views more  FUIN 2006»
14 years 10 months ago
Learning Sunspot Classification
Sunspots are the subject of interest to many astronomers and solar physicists. Sunspot observation, analysis and classification form an important part of furthering the knowledge a...
Trung Thanh Nguyen, Claire P. Willis, Derek J. Pad...