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» Arguing from Experience to Classifying Noisy Data
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MCS
2007
Springer
14 years 1 months ago
Selecting Diversifying Heuristics for Cluster Ensembles
Abstract. Cluster ensembles are deemed to be better than single clustering algorithms for discovering complex or noisy structures in data. Various heuristics for constructing such ...
Stefan Todorov Hadjitodorov, Ludmila I. Kuncheva
AND
2010
13 years 5 months ago
Reshaping automatic speech transcripts for robust high-level spoken document analysis
High-level spoken document analysis is required in many applications seeking access to the semantic content of audio data, such as information retrieval, machine translation or au...
Julien Fayolle, Fabienne Moreau, Christian Raymond...
ICPR
2008
IEEE
14 years 8 months ago
Multiple view based 3D object classification using ensemble learning of local subspaces
Multiple observation improves the performance of 3D object classification. However, since the distribution of feature vectors obtained from multiple view points have strong nonlin...
Jianing Wu, Kazuhiro Fukui
AIRS
2005
Springer
14 years 1 months ago
A Probabilistic Model for Music Recommendation Considering Audio Features
In order to make personalized recommendations, many collaborative music recommender systems (CMRS) focused on capturing precise similarities among users or items based on user hist...
Qing Li, Sung-Hyon Myaeng, Donghai Guan, Byeong Ma...
ECCV
2008
Springer
13 years 9 months ago
Multiple Instance Boost Using Graph Embedding Based Decision Stump for Pedestrian Detection
Pedestrian detection in still image should handle the large appearance and stance variations arising from the articulated structure, various clothing of human as well as viewpoints...
Junbiao Pang, Qingming Huang, Shuqiang Jiang