Sciweavers

Share
18 search results - page 1 / 4
» A Learning Algorithm for Localizing People Based on Wireless...
Sort
View
IJCAI
2003
11 years 2 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...
IJCAI
2007
11 years 2 months ago
WiFi-SLAM Using Gaussian Process Latent Variable Models
WiFi localization, the task of determining the physical location of a mobile device from wireless signal strengths, has been shown to be an accurate method of indoor and outdoor l...
Brian Ferris, Dieter Fox, Neil D. Lawrence
TMC
2008
123views more  TMC 2008»
11 years 1 months ago
Learning Adaptive Temporal Radio Maps for Signal-Strength-Based Location Estimation
In wireless networks, a client's locations can be estimated using signal strength received from signal transmitters. Static fingerprint-based techniques are commonly used for ...
Jie Yin, Qiang Yang, Lionel M. Ni
PERCOM
2005
ACM
12 years 29 days ago
Reducing the Calibration Effort for Location Estimation Using Unlabeled Samples
WLAN location estimation based on 802.11 signal strength is becoming increasingly prevalent in today's pervasive computing applications. As alternative to the wellestablished...
Xiaoyong Chai, Qiang Yang
COLING
2008
11 years 2 months ago
Homotopy-Based Semi-Supervised Hidden Markov Models for Sequence Labeling
This paper explores the use of the homotopy method for training a semi-supervised Hidden Markov Model (HMM) used for sequence labeling. We provide a novel polynomial-time algorith...
Gholamreza Haffari, Anoop Sarkar
books