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ISPASS
2009
IEEE
15 years 10 months ago
Lonestar: A suite of parallel irregular programs
Until recently, parallel programming has largely focused on the exploitation of data-parallelism in dense matrix programs. However, many important application domains, including m...
Milind Kulkarni, Martin Burtscher, Calin Cascaval,...
116
Voted
KDD
2008
ACM
110views Data Mining» more  KDD 2008»
16 years 3 months ago
Mining preferences from superior and inferior examples
Mining user preferences plays a critical role in many important applications such as customer relationship management (CRM), product and service recommendation, and marketing camp...
Bin Jiang, Jian Pei, Xuemin Lin, David W. Cheung, ...
136
Voted
AAAI
2010
15 years 4 months ago
Cost-Sensitive Semi-Supervised Support Vector Machine
In this paper, we study cost-sensitive semi-supervised learning where many of the training examples are unlabeled and different misclassification errors are associated with unequa...
Yu-Feng Li, James T. Kwok, Zhi-Hua Zhou
116
Voted
IJCNN
2006
IEEE
15 years 9 months ago
Nominal-scale Evolving Connectionist Systems
— A method is presented for extending the Evolving Connectionist System (ECoS) algorithm that allows it to explicitly represent and learn nominal-scale data without the need for ...
Michael J. Watts
124
Voted
ISI
2005
Springer
15 years 9 months ago
Private Mining of Association Rules
This paper introduces a new approach to a problem of data sharing among multiple parties, without disclosing the data between the parties. Our focus is data sharing among two parti...
Justin Z. Zhan, Stan Matwin, LiWu Chang