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KDD
2008
ACM
137views Data Mining» more  KDD 2008»
14 years 8 months ago
Learning classifiers from only positive and unlabeled data
The input to an algorithm that learns a binary classifier normally consists of two sets of examples, where one set consists of positive examples of the concept to be learned, and ...
Charles Elkan, Keith Noto
PRIB
2009
Springer
209views Bioinformatics» more  PRIB 2009»
14 years 2 months ago
Class Prediction from Disparate Biological Data Sources Using an Iterative Multi-Kernel Algorithm
For many biomedical modelling tasks a number of different types of data may influence predictions made by the model. An established approach to pursuing supervised learning with ...
Yiming Ying, Colin Campbell, Theodoros Damoulas, M...
ATAL
2009
Springer
14 years 2 months ago
Learning a model of speaker head nods using gesture corpora
During face-to-face conversation, the speaker’s head is continually in motion. These movements serve a variety of important communicative functions. Our goal is to develop a mod...
Jina Lee, Stacy Marsella
SIGMOD
2012
ACM
242views Database» more  SIGMOD 2012»
11 years 10 months ago
Dynamic management of resources and workloads for RDBMS in cloud: a control-theoretic approach
As cloud computing environments become explosively popular, dealing with unpredictable changes, uncertainties, and disturbances in both systems and environments turns out to be on...
Pengcheng Xiong
ECSA
2010
Springer
13 years 8 months ago
Learning from the Cell Life-Cycle: A Self-adaptive Paradigm
In the software domain, self-adaptive systems are able to modify their behavior at run-time to respond to changes in the environment they run, to changes of the users' require...
Antinisca Di Marco, Francesco Gallo, Paola Inverar...