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KDD
2010
ACM
224views Data Mining» more  KDD 2010»
14 years 2 months ago
Multi-label learning by exploiting label dependency
In multi-label learning, each training example is associated with a set of labels and the task is to predict the proper label set for the unseen example. Due to the tremendous (ex...
Min-Ling Zhang, Kun Zhang
IJCAI
2003
13 years 11 months ago
Statistics Gathering for Learning from Distributed, Heterogeneous and Autonomous Data Sources
With the growing use of distributed information networks, there is an increasing need for algorithmic and system solutions for data-driven knowledge acquisition using distributed,...
Doina Caragea, Jaime Reinoso, Adrian Silvescu, Vas...
PKDD
2010
Springer
313views Data Mining» more  PKDD 2010»
13 years 8 months ago
Topic Modeling for Personalized Recommendation of Volatile Items
One of the major strengths of probabilistic topic modeling is the ability to reveal hidden relations via the analysis of co-occurrence patterns on dyadic observations, such as docu...
Maks Ovsjanikov, Ye Chen
TASE
2008
IEEE
13 years 9 months ago
An Intelligent Online Monitoring and Diagnostic System for Manufacturing Automation
Condition monitoring and fault diagnosis in modern manufacturing automation is of great practical significance. It improves quality and productivity, and prevents damage to machine...
Ming Ge, Yangsheng Xu, Ruxu Du
SDM
2007
SIAM
81views Data Mining» more  SDM 2007»
13 years 11 months ago
A PAC Bound for Approximate Support Vector Machines
We study a class of algorithms that speed up the training process of support vector machines (SVMs) by returning an approximate SVM. We focus on algorithms that reduce the size of...
Dongwei Cao, Daniel Boley