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» The Tradeoffs of Large Scale Learning
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ICML
2010
IEEE
13 years 9 months ago
Large Graph Construction for Scalable Semi-Supervised Learning
In this paper, we address the scalability issue plaguing graph-based semi-supervised learning via a small number of anchor points which adequately cover the entire point cloud. Cr...
Wei Liu, Junfeng He, Shih-Fu Chang
ICML
2010
IEEE
13 years 5 months ago
Learning optimally diverse rankings over large document collections
Most learning to rank research has assumed that the utility of different documents is independent, which results in learned ranking functions that return redundant results. The fe...
Aleksandrs Slivkins, Filip Radlinski, Sreenivas Go...
DAGM
2004
Springer
14 years 1 months ago
Scale-Invariant Object Categorization Using a Scale-Adaptive Mean-Shift Search
The goal of our work is object categorization in real-world scenes. That is, given a novel image we want to recognize and localize unseen-before objects based on their similarity t...
Bastian Leibe, Bernt Schiele
ESWS
2009
Springer
14 years 2 months ago
Improving Ontology Matching Using Meta-level Learning
Despite serious research efforts, automatic ontology matching still suffers from severe problems with respect to the quality of matching results. Existing matching systems trade-of...
Kai Eckert, Christian Meilicke, Heiner Stuckenschm...
ICIP
2001
IEEE
14 years 9 months ago
Face detection using large margin classifiers
Large margin classifiers have demonstrated their advantages in many visual learning tasks, and have attracted much attention in vision and image processing communities. In this pa...
Ming-Hsuan Yang, Dan Roth, Narendra Ahuja