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IROS
2008
IEEE
125views Robotics» more  IROS 2008»
13 years 11 months ago
Neighborhood denoising for learning high-dimensional grasping manifolds
— Human control of high degree-of-freedom robotic systems, e.g. anthropomorphic robot hands, is often difficult due to the overwhelming number of variables that need to be speci...
Aggeliki Tsoli, Odest Chadwicke Jenkins
ACL
2006
13 years 6 months ago
Modeling Commonality among Related Classes in Relation Extraction
This paper proposes a novel hierarchical learning strategy to deal with the data sparseness problem in relation extraction by modeling the commonality among related classes. For e...
Guodong Zhou, Jian Su, Min Zhang
KDD
2008
ACM
259views Data Mining» more  KDD 2008»
14 years 5 months ago
Using ghost edges for classification in sparsely labeled networks
We address the problem of classification in partially labeled networks (a.k.a. within-network classification) where observed class labels are sparse. Techniques for statistical re...
Brian Gallagher, Hanghang Tong, Tina Eliassi-Rad, ...
CVPR
2008
IEEE
14 years 6 months ago
Transfer learning for image classification with sparse prototype representations
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...
Ariadna Quattoni, Michael Collins, Trevor Darrell
ICML
2007
IEEE
14 years 5 months ago
Sparse eigen methods by D.C. programming
Eigenvalue problems are rampant in machine learning and statistics and appear in the context of classification, dimensionality reduction, etc. In this paper, we consider a cardina...
Bharath K. Sriperumbudur, David A. Torres, Gert R....