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BMCBI
2006
173views more  BMCBI 2006»
13 years 7 months ago
Kernel-based distance metric learning for microarray data classification
Background: The most fundamental task using gene expression data in clinical oncology is to classify tissue samples according to their gene expression levels. Compared with tradit...
Huilin Xiong, Xue-wen Chen
ICRA
2007
IEEE
178views Robotics» more  ICRA 2007»
14 years 1 months ago
Behavior Based Adaptive Control for Autonomous Oceanographic Sampling
Abstract— This paper describes an investigation into the adaptive control of autonomous mobile sensor platforms for providing oceanographic sampling. Mobile sensor platforms prov...
Donald P. Eickstedt, Michael R. Benjamin, Ding Wan...
JMLR
2006
99views more  JMLR 2006»
13 years 7 months ago
Worst-Case Analysis of Selective Sampling for Linear Classification
A selective sampling algorithm is a learning algorithm for classification that, based on the past observed data, decides whether to ask the label of each new instance to be classi...
Nicolò Cesa-Bianchi, Claudio Gentile, Luca ...
CVPR
2010
IEEE
13 years 6 months ago
Rapid and accurate developmental stage recognition of C. elegans from high-throughput image data
We present a hierarchical principle for object recognition and its application to automatically classify developmental stages of C. elegans animals from a population of mixed stag...
Amelia White, Huey-Ling Kao, Patricia Cipriani, Br...
CGF
2004
74views more  CGF 2004»
13 years 7 months ago
VOTS: VOlume doTS as a Point-Based Representation of Volumetric Data
We present Volume dots (Vots), a new primitive for volumetric data modelling, processing, and rendering. Vots are a point-based representation of volumetric data. An individual Vo...
Sören Grimm, Stefan Bruckner, Armin Kanitsar,...