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ALT
2009
Springer
16 years 22 days ago
Learning from Streams
Abstract. Learning from streams is a process in which a group of learners separately obtain information about the target to be learned, but they can communicate with each other in ...
Sanjay Jain, Frank Stephan, Nan Ye
KDD
2012
ACM
207views Data Mining» more  KDD 2012»
13 years 6 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
ICTAI
2006
IEEE
15 years 9 months ago
Improve Decision Trees for Probability-Based Ranking by Lazy Learners
Existing work shows that classic decision trees have inherent deficiencies in obtaining a good probability-based ranking (e.g. AUC). This paper aims to improve the ranking perfor...
Han Liang, Yuhong Yan
ER
2007
Springer
142views Database» more  ER 2007»
15 years 10 months ago
Automatic Hidden-Web Table Interpretation by Sibling Page Comparison
The longstanding problem of automatic table interpretation still illudes us. Its solution would not only be an aid to table processing applications such as large volume table conve...
Cui Tao, David W. Embley
ER
2007
Springer
129views Database» more  ER 2007»
15 years 10 months ago
A Methodology and Toolkit for Deploying Contract Documents as E-contracts
Recent research in e-contracts is concerned with the development of frameworks and tools to support contracts. EREC framework is one that enables modelling and deployment of e-con...
Anushree Khandekar, P. Radha Krishna, Kamalakar Ka...