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IJCAI
2007
15 years 7 months ago
Managing Domain Knowledge and Multiple Models with Boosting
We present MBoost, a novel extension to AdaBoost that extends boosting to use multiple weak learners explicitly, and provides robustness to learning models that overfit or are po...
Peng Zang, Charles Lee Isbell Jr.
ICCV
2009
IEEE
16 years 11 months ago
Unlabeled data improves word prediction
Labeling image collections is a tedious task, especially when multiple labels have to be chosen for each image. In this paper we introduce a new framework that extends state of ...
Nicolas Loeff, Ali Farhadi, Ian Endres and David A...
ESWS
2009
Springer
16 years 27 days ago
An Ontology of Resources: Solving the Identity Crisis
The primary goal of the Semantic Web is to use URIs as a universal space to name anything, expanding from using URIs for webpages to URIs for “real objects and imaginary concepts...
Harry Halpin, Valentina Presutti
GECCO
2006
Springer
192views Optimization» more  GECCO 2006»
15 years 10 months ago
Optimising cancer chemotherapy using an estimation of distribution algorithm and genetic algorithms
This paper presents a methodology for using heuristic search methods to optimise cancer chemotherapy. Specifically, two evolutionary algorithms - Population Based Incremental Lear...
Andrei Petrovski, Siddhartha Shakya, John A. W. Mc...
CVPR
2010
IEEE
16 years 2 months ago
Safety in Numbers: Learning Categories from Few Examples with Multi Model Knowledge Transfer
Learning object categories from small samples is a challenging problem, where machine learning tools can in general provide very few guarantees. Exploiting prior knowledge may be ...
Tatiana Tommasi, Francesco Orabona, Barbara Caputo