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» MILIS: Multiple Instance Learning with Instance Selection
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ICDM
2009
IEEE
137views Data Mining» more  ICDM 2009»
14 years 3 months ago
Set-Based Boosting for Instance-Level Transfer
—The success of transfer to improve learning on a target task is highly dependent on the selected source data. Instance-based transfer methods reuse data from the source tasks to...
Eric Eaton, Marie desJardins
EMNLP
2011
12 years 8 months ago
Class Label Enhancement via Related Instances
Class-instance label propagation algorithms have been successfully used to fuse information from multiple sources in order to enrich a set of unlabeled instances with class labels...
Zornitsa Kozareva, Konstantin Voevodski, Shang-Hua...
ECML
2006
Springer
14 years 19 days ago
Margin-Based Active Learning for Structured Output Spaces
In many complex machine learning applications there is a need to learn multiple interdependent output variables, where knowledge of these interdependencies can be exploited to impr...
Dan Roth, Kevin Small
AAAI
2007
13 years 11 months ago
Combining Multiple Heuristics Online
We present black-box techniques for learning how to interleave the execution of multiple heuristics in order to improve average-case performance. In our model, a user is given a s...
Matthew J. Streeter, Daniel Golovin, Stephen F. Sm...
ATAL
2005
Springer
14 years 2 months ago
Agent-based trust model involving multiple qualities
A key limitation of current Web services standards is the inability to differentiate service instances at runtime using (nonfunctional) qualities of services (QoS). Such differe...
E. Michael Maximilien, Munindar P. Singh