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COOPIS
2004
IEEE
13 years 11 months ago
Learning Classifiers from Semantically Heterogeneous Data
Semantically heterogeneous and distributed data sources are quite common in several application domains such as bioinformatics and security informatics. In such a setting, each dat...
Doina Caragea, Jyotishman Pathak, Vasant Honavar
ICDM
2008
IEEE
112views Data Mining» more  ICDM 2008»
14 years 2 months ago
Supervised Inductive Learning with Lotka-Volterra Derived Models
We present a classification algorithm built on our adaptation of the Generalized Lotka-Volterra model, well-known in mathematical ecology. The training algorithm itself consists ...
Karen Hovsepian, Peter Anselmo, Subhasish Mazumdar
ICIAR
2004
Springer
14 years 27 days ago
A Fast Probabilistic Bidirectional Texture Function Model
The bidirectional texture function (BTF) describes rough texture appearance variations due to varying illumination and viewing conditions. Such a function consists of thousands of ...
Michal Haindl, Jirí Filip
IV
2006
IEEE
82views Visualization» more  IV 2006»
14 years 1 months ago
Two sides of the story: Visualising Products and Processes in Engineering Design
This paper describes research on the use of multiple views for modelling products and processes in the design of complex products. Single visual representations of design models o...
René Keller, Tomás L. Flanagan, Clau...
JMLR
2006
169views more  JMLR 2006»
13 years 7 months ago
Bayesian Network Learning with Parameter Constraints
The task of learning models for many real-world problems requires incorporating domain knowledge into learning algorithms, to enable accurate learning from a realistic volume of t...
Radu Stefan Niculescu, Tom M. Mitchell, R. Bharat ...