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IJCAI
2003
15 years 8 months ago
A Learning Algorithm for Localizing People Based on Wireless Signal Strength that Uses Labeled and Unlabeled Data
This paper summarizes a probabilistic approach for localizing people through the signal strengths of a wireless IEEE 802.11b network. Our approach uses data labeled by ground trut...
Sebastian Thrun, Geoffrey J. Gordon, Frank Pfennin...
CORR
2010
Springer
77views Education» more  CORR 2010»
15 years 6 months ago
Pattern Classification In Symbolic Streams via Semantic Annihilation of Information
We propose a technique for pattern classification in symbolic streams via selective erasure of observed symbols, in cases where the patterns of interest are represented as Probabil...
Ishanu Chattopadhyay, Yicheng Wen, Asok Ray
CORR
2000
Springer
67views Education» more  CORR 2000»
15 years 6 months ago
Recognition Performance of a Structured Language Model
A new language model for speech recognition inspired by linguistic analysis is presented. The model develops hidden hierarchical structure incrementally and uses it to extract mea...
Ciprian Chelba, Frederick Jelinek
CIKM
2008
Springer
15 years 8 months ago
A latent variable model for query expansion using the hidden markov model
We propose a novel probabilistic method based on the Hidden Markov Model (HMM) to learn the structure of a Latent Variable Model (LVM) for query language modeling. In the proposed...
Qiang Huang, Dawei Song
ICIP
2001
IEEE
16 years 8 months ago
EM algorithms of Gaussian mixture model and hidden Markov model
The HMM (Hidden Markov Model) is a probabilistic model of the joint probability of a collection of random variables with both observations and states. The GMM (Gaussian Mixture Mo...
Guorong Xuan, Wei Zhang, Peiqi Chai