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KDD
2006
ACM
129views Data Mining» more  KDD 2006»
16 years 3 months ago
Suppressing model overfitting in mining concept-drifting data streams
Mining data streams of changing class distributions is important for real-time business decision support. The stream classifier must evolve to reflect the current class distributi...
Haixun Wang, Jian Yin, Jian Pei, Philip S. Yu, Jef...
CVPR
1998
IEEE
16 years 5 months ago
Using Adaptive Tracking to Classify and Monitor Activities in a Site
We describe a vision system that monitors activity in a site over extended periods of time. The system uses a distributed set of sensors to cover the site, and an adaptive tracker...
W. Eric L. Grimson, Chris Stauffer, R. Romano, L. ...
134
Voted
KDD
2004
ACM
196views Data Mining» more  KDD 2004»
16 years 3 months ago
Adversarial classification
Essentially all data mining algorithms assume that the datagenerating process is independent of the data miner's activities. However, in many domains, including spam detectio...
Nilesh N. Dalvi, Pedro Domingos, Mausam, Sumit K. ...
147
Voted
CVPR
2004
IEEE
16 years 5 months ago
Detecting and Reading Text in Natural Scenes
This paper gives an algorithm for detecting and reading text in natural images. The algorithm is intended for use by blind and visually impaired subjects walking through city scen...
Xiangrong Chen, Alan L. Yuille
152
Voted
AVBPA
2003
Springer
133views Biometrics» more  AVBPA 2003»
15 years 7 months ago
LUT-Based Adaboost for Gender Classification
There are two main approaches to the problem of gender classification, Support Vector Machines (SVMs) and Adaboost learning methods, of which SVMs are better in correct rate but ar...
Bo Wu, Haizhou Ai, Chang Huang