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» A New Framework for Dissimilarity and Similarity Learning
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ICML
2007
IEEE
15 years 10 months ago
Boosting for transfer learning
Traditional machine learning makes a basic assumption: the training and test data should be under the same distribution. However, in many cases, this identicaldistribution assumpt...
Wenyuan Dai, Qiang Yang, Gui-Rong Xue, Yong Yu
MMS
2010
14 years 8 months ago
Asynchronous reflections: theory and practice in the design of multimedia mirror systems
-- In this paper, we present a theoretical framing of the functions of a mirror by breaking the synchrony between the state of a reference object and its reflection. This framing p...
Wei Zhang, Bo Begole, Maurice Chu
96
Voted
IJCAI
2007
14 years 11 months ago
Building Portable Options: Skill Transfer in Reinforcement Learning
The options framework provides a method for reinforcement learning agents to build new high-level skills. However, since options are usually learned in the same state space as the...
George Konidaris, Andrew G. Barto
WWW
2008
ACM
15 years 10 months ago
Learning multiple graphs for document recommendations
The Web offers rich relational data with different semantics. In this paper, we address the problem of document recommendation in a digital library, where the documents in questio...
Ding Zhou, Shenghuo Zhu, Kai Yu, Xiaodan Song, Bel...
CVPR
2010
IEEE
15 years 3 months ago
Putting local features on a Manifold
Local features have proven very useful for recognition. Manifold learning has proven to be a very powerful tool in data analysis. However, manifold learning application for imag...
Marwan Torki and Ahmed Elgammal