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CVPR
1999
IEEE
16 years 8 months ago
Time-Series Classification Using Mixed-State Dynamic Bayesian Networks
We present a novel mixed-state dynamic Bayesian network (DBN) framework for modeling and classifying timeseries data such as object trajectories. A hidden Markov model (HMM) of di...
Vladimir Pavlovic, Brendan J. Frey, Thomas S. Huan...
ICANN
2001
Springer
15 years 10 months ago
Independent Variable Group Analysis
Humans tend to group together related properties in order to understand complex phenomena. When modeling large problems with limited representational resources, it is important to...
Krista Lagus, Esa Alhoniemi, Harri Valpola
SIGIR
2011
ACM
14 years 9 months ago
Parameterized concept weighting in verbose queries
The majority of the current information retrieval models weight the query concepts (e.g., terms or phrases) in an unsupervised manner, based solely on the collection statistics. I...
Michael Bendersky, Donald Metzler, W. Bruce Croft
TON
2010
167views more  TON 2010»
15 years 1 months ago
A Machine Learning Approach to TCP Throughput Prediction
TCP throughput prediction is an important capability in wide area overlay and multi-homed networks where multiple paths may exist between data sources and receivers. In this paper...
Mariyam Mirza, Joel Sommers, Paul Barford, Xiaojin...
CRV
2011
IEEE
305views Robotics» more  CRV 2011»
14 years 6 months ago
Motion Segmentation by Learning Homography Matrices from Motor Signals
—Motion information is an important cue for a robot to separate foreground moving objects from the static background world. Based on the observation that the motion of the backgr...
Changhai Xu, Jingen Liu, Benjamin Kuipers