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» Learning Patterns in Noisy Data: The AQ Approach
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ICPR
2006
IEEE
16 years 5 months ago
Shape Alignment by Learning a Landmark-PDM Coupled Model
This paper revisits the model-based approaches for groupwise shape alignment. The key contribution is modeling the landmarks instead of considering them as nodes sliding along the...
Yifeng Jiang, Jun Xie, Hung-Tat Tsui
127
Voted
ALT
2003
Springer
15 years 8 months ago
Can Learning in the Limit Be Done Efficiently?
Abstract. Inductive inference can be considered as one of the fundamental paradigms of algorithmic learning theory. We survey results recently obtained and show their impact to pot...
Thomas Zeugmann
CVPR
2005
IEEE
16 years 6 months ago
Pruning Training Sets for Learning of Object Categories
Training datasets for learning of object categories are often contaminated or imperfect. We explore an approach to automatically identify examples that are noisy or troublesome fo...
Anelia Angelova, Yaser S. Abu-Mostafa, Pietro Pero...
131
Voted
JMLR
2010
172views more  JMLR 2010»
14 years 11 months ago
Modeling annotator expertise: Learning when everybody knows a bit of something
Supervised learning from multiple labeling sources is an increasingly important problem in machine learning and data mining. This paper develops a probabilistic approach to this p...
Yan Yan, Rómer Rosales, Glenn Fung, Mark W....
176
Voted
CVPR
2010
IEEE
16 years 19 days ago
Data Fusion through Cross-modality Metric Learning using Similarity-Sensitive Hashing
Visual understanding is often based on measuring similarity between observations. Learning similarities specific to a certain perception task from a set of examples has been show...
Michael Bronstein, Alexander Bronstein, Nikos Para...