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» MILIS: Multiple Instance Learning with Instance Selection
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ICTAI
2007
IEEE
14 years 2 months ago
On Portfolios for Backtracking Search in the Presence of Deadlines
Constraint satisfaction and propositional satisfiability problems are often solved using backtracking search. Previous studies have shown that portfolios of backtracking algorith...
Huayue Wu, Peter van Beek
CVPR
2011
IEEE
13 years 4 months ago
Learning to Recognize Objects in Egocentric Activities
This paper addresses the problem of learning object models from egocentric video of household activities, using extremely weak supervision. For each activity sequence, we know onl...
Alireza Fathi, Xiaofeng Ren, James Rehg
ICDE
2012
IEEE
252views Database» more  ICDE 2012»
11 years 10 months ago
Approximate String Membership Checking: A Multiple Filter, Optimization-Based Approach
— We consider the approximate string membership checking (ASMC) problem of extracting all the strings or substrings in a document that approximately match some string in a given ...
Chong Sun, Jeffrey F. Naughton, Siddharth Barman
CVPR
2010
IEEE
13 years 5 months ago
Multi-structure model selection via kernel optimisation
Our goal is to fit the multiple instances (or structures) of a generic model existing in data. Here we propose a novel model selection scheme to estimate the number of genuine str...
Tat-Jun Chin, David Suter, Hanzi Wang
KDD
2009
ACM
227views Data Mining» more  KDD 2009»
14 years 8 months ago
Efficiently learning the accuracy of labeling sources for selective sampling
Many scalable data mining tasks rely on active learning to provide the most useful accurately labeled instances. However, what if there are multiple labeling sources (`oracles...
Pinar Donmez, Jaime G. Carbonell, Jeff Schneider