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KDD
2008
ACM
120views Data Mining» more  KDD 2008»
14 years 8 months ago
Multi-class cost-sensitive boosting with p-norm loss functions
We propose a family of novel cost-sensitive boosting methods for multi-class classification by applying the theory of gradient boosting to p-norm based cost functionals. We establ...
Aurelie C. Lozano, Naoki Abe
KDD
2008
ACM
140views Data Mining» more  KDD 2008»
14 years 8 months ago
On updates that constrain the features' connections during learning
In many multiclass learning scenarios, the number of classes is relatively large (thousands,...), or the space and time efficiency of the learning system can be crucial. We invest...
Omid Madani, Jian Huang 0002
WSDM
2010
ACM
210views Data Mining» more  WSDM 2010»
14 years 5 months ago
Leveraging Temporal Dynamics of Document Content in Relevance Ranking
Many web documents are dynamic, with content changing in varying amounts at varying frequencies. However, current document search algorithms have a static view of the document con...
Jonathan L. Elsas, Susan T. Dumais
ICDM
2009
IEEE
117views Data Mining» more  ICDM 2009»
14 years 2 months ago
Clustering with Multiple Graphs
—In graph-based learning models, entities are often represented as vertices in an undirected graph with weighted edges describing the relationships between entities. In many real...
Wei Tang, Zhengdong Lu, Inderjit S. Dhillon
PKDD
2009
Springer
117views Data Mining» more  PKDD 2009»
14 years 2 months ago
New Regularized Algorithms for Transductive Learning
Abstract. We propose a new graph-based label propagation algorithm for transductive learning. Each example is associated with a vertex in an undirected graph and a weighted edge be...
Partha Pratim Talukdar, Koby Crammer