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» Evaluating algorithms that learn from data streams
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KDD
2008
ACM
110views Data Mining» more  KDD 2008»
16 years 7 months ago
Mining preferences from superior and inferior examples
Mining user preferences plays a critical role in many important applications such as customer relationship management (CRM), product and service recommendation, and marketing camp...
Bin Jiang, Jian Pei, Xuemin Lin, David W. Cheung, ...
LREC
2008
180views Education» more  LREC 2008»
15 years 8 months ago
Do we Still Need Gold Standards for Evaluation?
The availability of a huge mass of textual data in electronic format has increased the need for fast and accurate techniques for textual data processing. Machine learning and stat...
Thierry Poibeau, Cédric Messiant
ML
2006
ACM
15 years 6 months ago
Relational IBL in classical music
It is well known that many hard tasks considered in machine learning and data mining can be solved in a rather simple and robust way with an instanceand distance-based approach. In...
Asmir Tobudic, Gerhard Widmer
DOCENG
2006
ACM
16 years 17 days ago
Evaluating invariances in document layout functions
With the development of variable-data-driven digital presses where each document printed is potentially unique there is a need for pre-press optimization to identify material that...
Alexander J. Macdonald, David F. Brailsford, John ...
DAGM
2011
Springer
14 years 6 months ago
Multiple Instance Boosting for Face Recognition in Videos
For face recognition from video streams often cues such as transcripts, subtitles or on-screen text are available. This information could be very valuable for improving the recogni...
Paul Wohlhart, Martin Köstinger, Peter M. Rot...