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» On Using Learning Curves to Evaluate ITS
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ECCV
2008
Springer
14 years 10 months ago
Weakly Supervised Object Localization with Stable Segmentations
Multiple Instance Learning (MIL) provides a framework for training a discriminative classifier from data with ambiguous labels. This framework is well suited for the task of learni...
Carolina Galleguillos, Boris Babenko, Andrew Rabin...
ICML
2004
IEEE
14 years 9 months ago
Solving cluster ensemble problems by bipartite graph partitioning
A critical problem in cluster ensemble research is how to combine multiple clusterings to yield a final superior clustering result. Leveraging advanced graph partitioning techniqu...
Xiaoli Zhang Fern, Carla E. Brodley
KDD
2002
ACM
171views Data Mining» more  KDD 2002»
14 years 8 months ago
Mining complex models from arbitrarily large databases in constant time
In this paper we propose a scaling-up method that is applicable to essentially any induction algorithm based on discrete search. The result of applying the method to an algorithm ...
Geoff Hulten, Pedro Domingos
SIGIR
2009
ACM
14 years 2 months ago
An improved markov random field model for supporting verbose queries
Recent work in supervised learning of term-based retrieval models has shown significantly improved accuracy can often be achieved via better model estimation [2, 10, 11, 17]. In ...
Matthew Lease
CCS
2007
ACM
14 years 2 months ago
Privacy-preserving remote diagnostics
We present an efficient protocol for privacy-preserving evaluation of diagnostic programs, represented as binary decision trees or branching programs. The protocol applies a bran...
Justin Brickell, Donald E. Porter, Vitaly Shmatiko...