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CIKM
2009
Springer
13 years 8 months ago
Mining data streams with periodically changing distributions
Dynamic data streams are those whose underlying distribution changes over time. They occur in a number of application domains, and mining them is important for these applications....
Yingying Tao, M. Tamer Özsu
PAMI
2008
302views more  PAMI 2008»
13 years 5 months ago
Learning to Detect Moving Shadows in Dynamic Environments
We propose a novel adaptive technique for detecting moving shadows and distinguishing them from moving objects in video sequences. Most methods for detecting shadows work in a stat...
Ajay J. Joshi, Nikolaos Papanikolopoulos
ICRA
2007
IEEE
147views Robotics» more  ICRA 2007»
13 years 11 months ago
Classification-Based Wheel Slip Detection and Detector Fusion for Outdoor Mobile Robots
— This paper introduces a signal-recognition based approach for detecting autonomous mobile robot immobilization on outdoor terrain. The technique utilizes a support vector machi...
Chris C. Ward, Karl Iagnemma
ICDM
2010
IEEE
142views Data Mining» more  ICDM 2010»
13 years 3 months ago
Causal Discovery from Streaming Features
In this paper, we study a new research problem of causal discovery from streaming features. A unique characteristic of streaming features is that not all features can be available ...
Kui Yu, Xindong Wu, Hao Wang, Wei Ding
KDD
2009
ACM
163views Data Mining» more  KDD 2009»
14 years 5 months ago
Large-scale graph mining using backbone refinement classes
We present a new approach to large-scale graph mining based on so-called backbone refinement classes. The method efficiently mines tree-shaped subgraph descriptors under minimum f...
Andreas Maunz, Christoph Helma, Stefan Kramer