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KDD
2012
ACM
207views Data Mining» more  KDD 2012»
11 years 9 months ago
Robust multi-task feature learning
Multi-task learning (MTL) aims to improve the performance of multiple related tasks by exploiting the intrinsic relationships among them. Recently, multi-task feature learning alg...
Pinghua Gong, Jieping Ye, Changshui Zhang
SIGMOD
2008
ACM
144views Database» more  SIGMOD 2008»
14 years 7 months ago
Mining significant graph patterns by leap search
With ever-increasing amounts of graph data from disparate sources, there has been a strong need for exploiting significant graph patterns with user-specified objective functions. ...
Xifeng Yan, Hong Cheng, Jiawei Han, Philip S. Yu
SAC
2009
ACM
14 years 2 months ago
Applying latent dirichlet allocation to group discovery in large graphs
This paper introduces LDA-G, a scalable Bayesian approach to finding latent group structures in large real-world graph data. Existing Bayesian approaches for group discovery (suc...
Keith Henderson, Tina Eliassi-Rad
CVPR
2010
IEEE
14 years 1 months ago
Weakly-Supervised Hashing in Kernel Space
The explosive growth of the vision data motivates the recent studies on efficient data indexing methods such as locality-sensitive hashing (LSH). Most existing approaches perform...
Yadong Mu, Jialie Shen, Shuicheng Yan
ICDCS
2002
IEEE
14 years 9 days ago
A Fully Distributed Framework for Cost-Sensitive Data Mining
Data mining systems aim to discover patterns and extract useful information from facts recorded in databases. A widely adopted approach is to apply machine learning algorithms to ...
Wei Fan, Haixun Wang, Philip S. Yu, Salvatore J. S...