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KDD
2009
ACM
180views Data Mining» more  KDD 2009»
16 years 6 months ago
Using graph-based metrics with empirical risk minimization to speed up active learning on networked data
Active and semi-supervised learning are important techniques when labeled data are scarce. Recently a method was suggested for combining active learning with a semi-supervised lea...
Sofus A. Macskassy
KDD
2009
ACM
188views Data Mining» more  KDD 2009»
16 years 6 months ago
Mining discrete patterns via binary matrix factorization
Mining discrete patterns in binary data is important for subsampling, compression, and clustering. We consider rankone binary matrix approximations that identify the dominant patt...
Bao-Hong Shen, Shuiwang Ji, Jieping Ye
ICFP
2007
ACM
16 years 6 months ago
A type system for recursive modules
There has been much work in recent years on extending ML with recursive modules. One of the most difficult problems in the development of such an extension is the double vision pr...
Derek Dreyer
MOBIHOC
2005
ACM
16 years 6 months ago
Localization and routing in sensor networks by local angle information
Location information is very useful in the design of sensor network infrastructures. In this paper, we study the anchor-free 2D localization problem by using local angle measureme...
Jehoshua Bruck, Jie Gao, Anxiao Jiang
ICS
2010
Tsinghua U.
16 years 3 months ago
Space-Efficient Estimation of Robust Statistics and Distribution Testing
: The generic problem of estimation and inference given a sequence of i.i.d. samples has been extensively studied in the statistics, property testing, and learning communities. A n...
Steve Chien, Katrina Ligett, Andrew McGregor