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KDD
2009
ACM
150views Data Mining» more  KDD 2009»
16 years 4 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 4 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
151
Voted
KDD
2006
ACM
200views Data Mining» more  KDD 2006»
16 years 4 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
130
Voted
KDD
2002
ACM
169views Data Mining» more  KDD 2002»
16 years 4 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»
15 years 10 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