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» A Boosting Approach to Multiple Instance Learning
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EMNLP
2011
12 years 7 months ago
Relation Extraction with Relation Topics
This paper describes a novel approach to the semantic relation detection problem. Instead of relying only on the training instances for a new relation, we leverage the knowledge l...
Chang Wang, James Fan, Aditya Kalyanpur, David Gon...
IJCV
2008
106views more  IJCV 2008»
13 years 7 months ago
Evaluation of Localized Semantics: Data, Methodology, and Experiments
We present a new data set encoding localized semantics for 1014 images and a methodology for using this kind of data for recognition evaluation. This methodology establishes protoc...
Kobus Barnard, Quanfu Fan, Ranjini Swaminathan, An...
MLDM
2007
Springer
14 years 1 months ago
Transductive Learning from Relational Data
Transduction is an inference mechanism “from particular to particular”. Its application to classification tasks implies the use of both labeled (training) data and unlabeled (...
Michelangelo Ceci, Annalisa Appice, Nicola Barile,...
CORR
2011
Springer
185views Education» more  CORR 2011»
13 years 2 months ago
Large-Scale Collective Entity Matching
There have been several recent advancements in Machine Learning community on the Entity Matching (EM) problem. However, their lack of scalability has prevented them from being app...
Vibhor Rastogi, Nilesh N. Dalvi, Minos N. Garofala...
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