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» Data Mining: Machine Learning, Statistics, and Databases
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ML
2010
ACM
142views Machine Learning» more  ML 2010»
15 years 13 hour ago
Fast adaptive algorithms for abrupt change detection
We propose two fast algorithms for abrupt change detection in streaming data that can operate on arbitrary unknown data distributions before and after the change. The first algor...
Daniel Nikovski, Ankur Jain
ISMB
1993
15 years 2 months ago
Transmembrane Segment Prediction from Protein Sequence Data
Weconsider tile automatedidentification of transmembrane domains in membrane protein sequences. 324 proteins (containing 1585 segrrmnts) werc examined, representing every protein ...
Sholom M. Weiss, Dawn M. Cohen, Nitin Indurkhya
122
Voted
WSDM
2012
ACM
259views Data Mining» more  WSDM 2012»
13 years 9 months ago
Learning recommender systems with adaptive regularization
Many factorization models like matrix or tensor factorization have been proposed for the important application of recommender systems. The success of such factorization models dep...
Steffen Rendle
131
Voted
KDD
2009
ACM
211views Data Mining» more  KDD 2009»
16 years 2 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,...
KDD
2006
ACM
134views Data Mining» more  KDD 2006»
16 years 2 months ago
Learning to rank networked entities
Several algorithms have been proposed to learn to rank entities modeled as feature vectors, based on relevance feedback. However, these algorithms do not model network connections...
Alekh Agarwal, Soumen Chakrabarti, Sunny Aggarwal