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» On Markov Chains for Independent Sets
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SADM
2010
196views more  SADM 2010»
13 years 2 months ago
Bayesian adaptive nearest neighbor
: The k nearest neighbor classification (k-NN) is a very simple and popular method for classification. However, it suffers from a major drawback, it assumes constant local class po...
Ruixin Guo, Sounak Chakraborty
SDM
2011
SIAM
256views Data Mining» more  SDM 2011»
12 years 10 months ago
Temporal Structure Learning for Clustering Massive Data Streams in Real-Time
This paper describes one of the first attempts to model the temporal structure of massive data streams in real-time using data stream clustering. Recently, many data stream clust...
Michael Hahsler, Margaret H. Dunham
CVPR
2004
IEEE
14 years 9 months ago
Efficient Belief Propagation for Early Vision
Markov random field models provide a robust and unified framework for early vision problems such as stereo, optical flow and image restoration. Inference algorithms based on graph...
Pedro F. Felzenszwalb, Daniel P. Huttenlocher
ICML
2007
IEEE
14 years 8 months ago
Conditional random fields for multi-agent reinforcement learning
Conditional random fields (CRFs) are graphical models for modeling the probability of labels given the observations. They have traditionally been trained with using a set of obser...
Xinhua Zhang, Douglas Aberdeen, S. V. N. Vishwanat...
ICMCS
2005
IEEE
139views Multimedia» more  ICMCS 2005»
14 years 1 months ago
Rapid Feature Space Speaker Adaptation for Multi-Stream HMM-Based Audio-Visual Speech Recognition
Multi-stream hidden Markov models (HMMs) have recently been very successful in audio-visual speech recognition, where the audio and visual streams are fused at the final decision...
Jing Huang, Etienne Marcheret, Karthik Visweswaria...