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» Learning Classifiers from Semantically Heterogeneous Data
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CCGRID
2003
IEEE
14 years 2 months ago
An Exposed Approach to Reliable Multicast in Heterogeneous Logistical Networks
An exposed approach in computer service architecture is one that offers client software a primitive service whose semantics are closely based on the underlying physical infrastruc...
Micah Beck, Ying Ding 0002, Erika Fuentes, Sharmil...
ICPR
2004
IEEE
14 years 10 months ago
Learning Spatial Context from Tracking using Penalised Likelihoods
MAP estimation of Gaussian mixtures through maximisation of penalised likelihoods was used to learn models of spatial context. This enabled prior beliefs about the scale, orientat...
Hammadi Nait-Charif, Stephen J. McKenna
NIPS
2008
13 years 10 months ago
Beyond Novelty Detection: Incongruent Events, when General and Specific Classifiers Disagree
Unexpected stimuli are a challenge to any machine learning algorithm. Here we identify distinct types of unexpected events, focusing on 'incongruent events' when 'g...
Daphna Weinshall, Hynek Hermansky, Alon Zweig, Jie...
CVPR
2000
IEEE
14 years 11 months ago
Learning from One Example through Shared Densities on Transforms
We define a process called congealing in which elements of a dataset (images) are brought into correspondence with each other jointly, producing a data-defined model. It is based ...
Erik G. Miller, Nicholas E. Matsakis, Paul A. Viol...
ADC
2007
Springer
124views Database» more  ADC 2007»
14 years 3 months ago
Interoperability for Geospatial Analysis: a Semantics and Ontology-based Approach
Information extraction and integration from heterogeneous, autonomous data resources are major requirements for many spatial applications. Geospatial analysis for scientific disco...
Zarine Kemp, Lei Tan, Jacqueline L. Whalley