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KDD
2009
ACM
150views Data Mining» more  KDD 2009»
16 years 7 months ago
Information theoretic regularization for semi-supervised boosting
We present novel semi-supervised boosting algorithms that incrementally build linear combinations of weak classifiers through generic functional gradient descent using both labele...
Lei Zheng, Shaojun Wang, Yan Liu, Chi-Hoon Lee
KDD
2007
ACM
178views Data Mining» more  KDD 2007»
16 years 7 months ago
Density-based clustering for real-time stream data
Existing data-stream clustering algorithms such as CluStream are based on k-means. These clustering algorithms are incompetent to find clusters of arbitrary shapes and cannot hand...
Yixin Chen, Li Tu
KDD
2006
ACM
200views Data Mining» more  KDD 2006»
16 years 7 months ago
A Random-Walk Based Scoring Algorithm Applied to Recommender Engines
Recommender systems are an emerging technology that helps consumers find interesting products and useful resources. A recommender system makes personalized product suggestions by e...
Augusto Pucci, Marco Gori, Marco Maggini
KDD
2002
ACM
169views Data Mining» more  KDD 2002»
16 years 7 months ago
A Framework for Customizable Sports Video Management and Retrieval
Several domain specific approaches for sports video management have shown the benefits of integrating low- and high- level video contents in supporting more robust retrieval. Howev...
Dian Tjondronegoro, Yi-Ping Phoebe Chen, Binh Pham
ICDM
2009
IEEE
137views Data Mining» more  ICDM 2009»
16 years 1 months ago
Regression Learning Vector Quantization
— Learning Vector Quantization (LVQ) is a popular class of nearest prototype classifiers for multiclass classification. Learning algorithms from this family are widely used becau...
Mihajlo Grbovic, Slobodan Vucetic