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ICDM
2007
IEEE
132views Data Mining» more  ICDM 2007»
16 years 1 months ago
Learning What Makes a Society Tick
We present a machine learning methodology (models, algorithms, and experimental data) to discovering the agent dynamics that drive the evolution of the social groups in a communit...
Hung-Ching Chen, Mark K. Goldberg, Malik Magdon-Is...
FGR
2006
IEEE
147views Biometrics» more  FGR 2006»
16 years 26 days ago
Learning Sparse Features in Granular Space for Multi-View Face Detection
In this paper, a novel sparse feature set is introduced into the Adaboost learning framework for multi-view face detection (MVFD), and a learning algorithm based on heuristic sear...
Chang Huang, Haizhou Ai, Yuan Li, Shihong Lao
ICCAD
2006
IEEE
119views Hardware» more  ICCAD 2006»
16 years 25 days ago
Dynamic power management using machine learning
Dynamic power management (DPM) work proposed to date places inactive components into low power states using a single DPM policy. In contrast, we instead dynamically select among a...
Gaurav Dhiman, Tajana Simunic Rosing
IDA
2005
Springer
16 years 9 days ago
Learning Label Preferences: Ranking Error Versus Position Error
We consider the problem of learning a ranking function, that is a mapping from instances to rankings over a finite number of labels. Our learning method, referred to as ranking by...
Eyke Hüllermeier, Johannes Fürnkranz
MM
2004
ACM
124views Multimedia» more  MM 2004»
16 years 6 days ago
An online-optimized incremental learning framework for video semantic classification
This paper considers the problems of feature variation and concept uncertainty in typical learning-based video semantic classification schemes. We proposed a new online semantic c...
Jun Wu, Xian-Sheng Hua, HongJiang Zhang, Bo Zhang