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» Improving Cause Detection Systems with Active Learning
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CVPR
2009
IEEE
16 years 5 months ago
What's It Going to Cost You?: Predicting Effort vs. Informativeness for Multi-Label Image Annotations
Active learning strategies can be useful when manual labeling effort is scarce, as they select the most informative examples to be annotated first. However, for visual category ...
Sudheendra Vijayanarasimhan (University of Texas a...
BIBE
2007
IEEE
162views Bioinformatics» more  BIBE 2007»
15 years 4 months ago
An Investigation into the Feasibility of Detecting Microscopic Disease Using Machine Learning
— The prognosis for many cancers could be improved dramatically if they could be detected while still at the microscopic disease stage. We are investigating the possibility of de...
Mary Qu Yang, Jack Y. Yang
CATE
2004
107views Education» more  CATE 2004»
14 years 11 months ago
Maximising Dialogue in Lectures using Group Response Systems
Laurillard sees dialogue as a crucial component of learning and she states that it is almost impossible to achieve in lectures. This paper identifies eight impediments to dialogue...
Quintin I. Cutts, Gregor E. Kennedy, Chris Mitchel...
CORR
2010
Springer
143views Education» more  CORR 2010»
14 years 10 months ago
Dendritic Cells for Anomaly Detection
Artificial immune systems, more specifically the negative selection algorithm, have previously been applied to intrusion detection. The aim of this research is to develop an intrus...
Julie Greensmith, Jamie Twycross, Uwe Aickelin
CAISE
2011
Springer
14 years 1 months ago
Supporting Dynamic, People-Driven Processes through Self-learning of Message Flows
Abstract. Flexibility and automatic learning are key aspects to support users in dynamic business environments such as value chains across SMEs or when organizing a large event. Pr...
Christoph Dorn, Schahram Dustdar