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» Evaluating algorithms that learn from data streams
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CIKM
2010
Springer
15 years 4 months ago
Combining link and content for collective active learning
In this paper, we study a novel problem Collective Active Learning, in which we aim to select a batch set of "informative" instances from a networking data set to query ...
Lixin Shi, Yuhang Zhao, Jie Tang
ICCV
2009
IEEE
15 years 4 months ago
Efficient multi-label ranking for multi-class learning: Application to object recognition
Multi-label learning is useful in visual object recognition when several objects are present in an image. Conventional approaches implement multi-label learning as a set of binary...
Serhat Selcuk Bucak, Pavan Kumar Mallapragada, Ron...
ICDE
2007
IEEE
92views Database» more  ICDE 2007»
16 years 1 months ago
A Cost Model for Storing and Retrieving Data in Wireless Sensor Networks
Many applications require storing data in Wireless Sensor Networks (WSNs). For example, in environmental monitoring applications, WSN may archive sensor data for retrieval at peri...
Adesola Omotayo, Moustafa A. Hammad, Ken Barker
COLT
2010
Springer
15 years 4 months ago
Adaptive Subgradient Methods for Online Learning and Stochastic Optimization
We present a new family of subgradient methods that dynamically incorporate knowledge of the geometry of the data observed in earlier iterations to perform more informative gradie...
John Duchi, Elad Hazan, Yoram Singer
SIGMOD
2004
ACM
163views Database» more  SIGMOD 2004»
16 years 7 months ago
Constraint-Based XML Query Rewriting For Data Integration
We study the problem of answering queries through a target schema, given a set of mappings between one or more source schemas and this target schema, and given that the data is at...
Cong Yu, Lucian Popa