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KDD
2006
ACM
180views Data Mining» more  KDD 2006»
14 years 10 months ago
Learning the unified kernel machines for classification
Kernel machines have been shown as the state-of-the-art learning techniques for classification. In this paper, we propose a novel general framework of learning the Unified Kernel ...
Steven C. H. Hoi, Michael R. Lyu, Edward Y. Chang
ICASSP
2011
IEEE
13 years 1 months ago
Unsupervised determination of efficient Korean LVCSR units using a Bayesian Dirichlet process model
Korean is an agglutinative language that does not have explicit word boundaries. It is also a highly inflective language that exhibits severe coarticulation effects. These charac...
Sakriani Sakti, Andrew M. Finch, Ryosuke Isotani, ...
ATAL
2007
Springer
14 years 4 months ago
A framework for agent-based distributed machine learning and data mining
This paper proposes a framework for agent-based distributed machine learning and data mining based on (i) the exchange of meta-level descriptions of individual learning processes ...
Jan Tozicka, Michael Rovatsos, Michal Pechoucek
BMCBI
2007
207views more  BMCBI 2007»
13 years 10 months ago
Discovering biomarkers from gene expression data for predicting cancer subgroups using neural networks and relational fuzzy clus
Background: The four heterogeneous childhood cancers, neuroblastoma, non-Hodgkin lymphoma, rhabdomyosarcoma, and Ewing sarcoma present a similar histology of small round blue cell...
Nikhil R. Pal, Kripamoy Aguan, Animesh Sharma, Shu...
NAACL
2010
13 years 7 months ago
Taxonomy Learning Using Word Sense Induction
Taxonomies are an important resource for a variety of Natural Language Processing (NLP) applications. Despite this, the current stateof-the-art methods in taxonomy learning have d...
Ioannis P. Klapaftis, Suresh Manandhar