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UIST
2010
ACM
14 years 7 months ago
Designing adaptive feedback for improving data entry accuracy
Data quality is critical for many information-intensive applications. One of the best opportunities to improve data quality is during entry. USHER provides a theoretical, data-dri...
Kuang Chen, Joseph M. Hellerstein, Tapan S. Parikh
CVPR
2012
IEEE
13 years 5 days ago
RALF: A reinforced active learning formulation for object class recognition
Active learning aims to reduce the amount of labels required for classification. The main difficulty is to find a good trade-off between exploration and exploitation of the lab...
Sandra Ebert, Mario Fritz, Bernt Schiele
BPM
2008
Springer
143views Business» more  BPM 2008»
14 years 11 months ago
Mining Based on Learning from Process Change Logs
In today's dynamic business world economic success of an enterprise increasingly depends on its ability to react to internal and external changes in a quick and flexible way. ...
Chen Li, Manfred Reichert, Andreas Wombacher
TON
2010
126views more  TON 2010»
14 years 4 months ago
MAC Scheduling With Low Overheads by Learning Neighborhood Contention Patterns
Aggregate traffic loads and topology in multi-hop wireless networks may vary slowly, permitting MAC protocols to `learn' how to spatially coordinate and adapt contention patte...
Yung Yi, Gustavo de Veciana, Sanjay Shakkottai
AROBOTS
1999
110views more  AROBOTS 1999»
14 years 9 months ago
Self-Localization of Autonomous Robots by Hidden Representations
We present a framework for constructing representations of space in an autonomous agent which does not obtain any direct information about its location. Instead the algorithm relie...
J. Michael Herrmann, Klaus Pawelzik, Theo Geisel