Nonlinear total variation based noise removal algorithms
Proceedings of the eleventh annual international conference of the Center for Nonlinear Studies on Experimental mathematics : computational issues in nonlinear science: computational issues in nonlinear science
WLAN Location Determination via Clustering and Probability Distributions
PERCOM '03 Proceedings of the First IEEE International Conference on Pervasive Computing and Communications
A practical evaluation of radio signal strength for ranging-based localization
ACM SIGMOBILE Mobile Computing and Communications Review
Manifold Regularization: A Geometric Framework for Learning from Labeled and Unlabeled Examples
The Journal of Machine Learning Research
MoteTrack: a robust, decentralized approach to RF-based location tracking
Personal and Ubiquitous Computing
Pervasive and Mobile Computing
A manifold regularization approach to calibration reduction for sensor-network based tracking
AAAI'06 Proceedings of the 21st national conference on Artificial intelligence - Volume 1
Co-localization from labeled and unlabeled data using graph Laplacian
IJCAI'07 Proceedings of the 20th international joint conference on Artifical intelligence
Statistical learning theory for location fingerprinting in wireless LANs
Computer Networks: The International Journal of Computer and Telecommunications Networking
Indoor Localization Using Neural Networks with Location Fingerprints
ICANN '09 Proceedings of the 19th International Conference on Artificial Neural Networks: Part II
Learning with l1-graph for image analysis
IEEE Transactions on Image Processing
Semi-Supervised Learning
Semi-supervised learning for WLAN positioning
ICANN'11 Proceedings of the 21th international conference on Artificial neural networks - Volume Part I
Advanced support vector machines for 802.11 indoor location
Signal Processing
Proceedings of the 10th international conference on Mobile systems, applications, and services
Nonlocal Discrete Regularization on Weighted Graphs: A Framework for Image and Manifold Processing
IEEE Transactions on Image Processing
Locating in fingerprint space: wireless indoor localization with little human intervention
Proceedings of the 18th annual international conference on Mobile computing and networking
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Location fingerprinting is a common approach to indoor localization. For good accuracy, the training set of sample fingerprints, each mapping a fingerprint to a location, should be sufficiently large to be well-representative of the environment in terms of both spatial coverage and temporal coverage. Unfortunately, the task of collecting these samples can be tedious and labor-intensive because one must label each location that is being surveyed. On the other hand, fingerprints without location information are abundant and can easily be collected and so recent studies have tried to capitalize on these unlabeled fingerprints to improve the training set. The paper investigates how this goal can be achieved via graph regularization based on Total Variation (TV). TV is highly effective for semi-supervised learning in image processing but it is not clear whether its success can be transferred to indoor location fingerprinting.