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» Negative Results for Active Learning with Convex Losses
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ICDM
2009
IEEE
149views Data Mining» more  ICDM 2009»
14 years 1 months ago
Accelerated Gradient Method for Multi-task Sparse Learning Problem
—Many real world learning problems can be recast as multi-task learning problems which utilize correlations among different tasks to obtain better generalization performance than...
Xi Chen, Weike Pan, James T. Kwok, Jaime G. Carbon...
CIKM
2008
Springer
13 years 9 months ago
Active relevance feedback for difficult queries
Relevance feedback has been demonstrated to be an effective strategy for improving retrieval accuracy. The existing relevance feedback algorithms based on language models and vect...
Zuobing Xu, Ram Akella
ICDCS
2006
IEEE
14 years 1 months ago
A Loss and Queuing-Delay Controller for Router Buffer Management
— Active queue management (AQM) in routers has been proposed as a solution to some of the scalability issues associated with TCP’s pure end-to-end approach to congestion contro...
Long Le, Kevin Jeffay, F. Donelson Smith
ICML
2008
IEEE
14 years 7 months ago
Listwise approach to learning to rank: theory and algorithm
This paper aims to conduct a study on the listwise approach to learning to rank. The listwise approach learns a ranking function by taking individual lists as instances and minimi...
Fen Xia, Tie-Yan Liu, Jue Wang, Wensheng Zhang, Ha...
JMLR
2012
11 years 9 months ago
UPAL: Unbiased Pool Based Active Learning
In this paper we address the problem of pool based active learning, and provide an algorithm, called UPAL, that works by minimizing the unbiased estimator of the risk of a hypothe...
Ravi Ganti, Alexander Gray