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ICML
2005
IEEE
16 years 7 months ago
Predicting relative performance of classifiers from samples
This paper is concerned with the problem of predicting relative performance of classification algorithms. It focusses on methods that use results on small samples and discusses th...
Rui Leite, Pavel Brazdil
ECML
2007
Springer
16 years 26 days ago
Discriminative Sequence Labeling by Z-Score Optimization
Abstract. We consider a new discriminative learning approach to sequence labeling based on the statistical concept of the Z-score. Given a training set of pairs of hidden-observed ...
Elisa Ricci, Tijl De Bie, Nello Cristianini
ACL
2007
15 years 8 months ago
A Seed-driven Bottom-up Machine Learning Framework for Extracting Relations of Various Complexity
A minimally supervised machine learning framework is described for extracting relations of various complexity. Bootstrapping starts from a small set of n-ary relation instances as...
Feiyu Xu, Hans Uszkoreit, Hong Li
IAT
2010
IEEE
15 years 4 months ago
Collaborative Learning of Ontology Fragments by Co-operating Agents
Abstract--Collaborating agents require either prior agreement on the shared vocabularies that they use for communication, or some means of translating between their private ontolog...
Heather S. Packer, Nicholas Gibbins, Nicholas R. J...
MICRO
2009
IEEE
113views Hardware» more  MICRO 2009»
16 years 1 months ago
Portable compiler optimisation across embedded programs and microarchitectures using machine learning
Building an optimising compiler is a difficult and time consuming task which must be repeated for each generation of a microprocessor. As the underlying microarchitecture changes...
Christophe Dubach, Timothy M. Jones, Edwin V. Boni...