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» The Dark Side of Object Learning: Learning Objects
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106
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ICML
2010
IEEE
15 years 4 months ago
Deep Supervised t-Distributed Embedding
Deep learning has been successfully applied to perform non-linear embedding. In this paper, we present supervised embedding techniques that use a deep network to collapse classes....
Martin Renqiang Min, Laurens van der Maaten, Zinen...
123
Voted
IJCINI
2007
106views more  IJCINI 2007»
15 years 3 months ago
The OAR Model of Neural Informatics for Internal Knowledge Representation in the Brain
The cognitive models of information representation are fundamental research areas in cognitive informatics, which attempts to reveal the mechanisms and potential of the brain in l...
Yingxu Wang
157
Voted
CVPR
2011
IEEE
14 years 11 months ago
Random Field Topic Model for Semantic Region Analysis in Crowded Scenes from Tracklets
In this paper, a Random Field Topic (RFT) model is proposed for semantic region analysis from motions of objects in crowded scenes. Different from existing approaches of learning ...
Bolei Zhou, Xiaogang Wang
134
Voted
ACL
2012
13 years 6 months ago
Discriminative Pronunciation Modeling: A Large-Margin, Feature-Rich Approach
We address the problem of learning the mapping between words and their possible pronunciations in terms of sub-word units. Most previous approaches have involved generative modeli...
Hao Tang, Joseph Keshet, Karen Livescu
458
Voted
CVPR
2012
IEEE
13 years 5 months ago
A Unified Framework for Event Summarization and Rare Event Detection
A novel approach for event summarization and rare event detection is proposed. Unlike conventional methods that deal with event summarization and rare event detection independently...
Junseok Kwon and Kyoung Mu Lee