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ICANN
2011
Springer
12 years 11 months ago
Learning from Multiple Annotators with Gaussian Processes
Abstract. In many supervised learning tasks it can be costly or infeasible to obtain objective, reliable labels. We may, however, be able to obtain a large number of subjective, po...
Perry Groot, Adriana Birlutiu, Tom Heskes
KDD
2009
ACM
211views Data Mining» more  KDD 2009»
14 years 8 months ago
Address standardization with latent semantic association
Address standardization is a very challenging task in data cleansing. To provide better customer relationship management and business intelligence for customer-oriented cooperates...
Honglei Guo, Huijia Zhu, Zhili Guo, Xiaoxun Zhang,...
DMIN
2010
262views Data Mining» more  DMIN 2010»
13 years 6 months ago
SMO-Style Algorithms for Learning Using Privileged Information
Recently Vapnik et al. [11, 12, 13] introduced a new learning model, called Learning Using Privileged Information (LUPI). In this model, along with standard training data, the tea...
Dmitry Pechyony, Rauf Izmailov, Akshay Vashist, Vl...
SIGMOD
2008
ACM
131views Database» more  SIGMOD 2008»
14 years 8 months ago
Domain adaptation of information extraction models
Domain adaptation refers to the process of adapting an extraction model trained in one domain to another related domain with only unlabeled data. We present a brief survey of exis...
Rahul Gupta, Sunita Sarawagi
ECML
2007
Springer
14 years 2 months ago
Dual Strategy Active Learning
Abstract. Active Learning methods rely on static strategies for sampling unlabeled point(s). These strategies range from uncertainty sampling and density estimation to multi-factor...
Pinar Donmez, Jaime G. Carbonell, Paul N. Bennett