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ICDM
2002
IEEE
105views Data Mining» more  ICDM 2002»
15 years 4 months ago
Empirical Comparison of Various Reinforcement Learning Strategies for Sequential Targeted Marketing
We empirically evaluate the performance of various reinforcement learning methods in applications to sequential targeted marketing. In particular, we propose and evaluate a progre...
Naoki Abe, Edwin P. D. Pednault, Haixun Wang, Bian...
SDM
2010
SIAM
200views Data Mining» more  SDM 2010»
15 years 18 days ago
Residual Bayesian Co-clustering for Matrix Approximation
In recent years, matrix approximation for missing value prediction has emerged as an important problem in a variety of domains such as recommendation systems, e-commerce and onlin...
Hanhuai Shan, Arindam Banerjee
SDM
2008
SIAM
140views Data Mining» more  SDM 2008»
15 years 17 days ago
Large-Scale Many-Class 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, Michael Connor
ICDM
2010
IEEE
150views Data Mining» more  ICDM 2010»
14 years 9 months ago
Detecting Novel Discrepancies in Communication Networks
Abstract--We address the problem of detecting characteristic patterns in communication networks. We introduce a scalable approach based on set-system discrepancy. By implicitly lab...
James Abello, Tina Eliassi-Rad, Nishchal Devanur
92
Voted
ICDM
2010
IEEE
172views Data Mining» more  ICDM 2010»
14 years 9 months ago
Learning Attribute-to-Feature Mappings for Cold-Start Recommendations
Cold-start scenarios in recommender systems are situations in which no prior events, like ratings or clicks, are known for certain users or items. To compute predictions in such ca...
Zeno Gantner, Lucas Drumond, Christoph Freudenthal...