A semi-supervised learning approach for robust indoor-outdoor detection with smartphones
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Mahesh K. Marina | Rik Sarkar | Panagiota Katsikouli | Valentin Radu | M. Marina | Valentin Radu | P. Katsikouli | Rik Sarkar
[1] Avrim Blum,et al. The Bottleneck , 2021, Monopsony Capitalism.
[2] Hojung Cha,et al. Smartphone-based Wi-Fi tracking system exploiting the RSS peak to overcome the RSS variance problem , 2013, Pervasive Mob. Comput..
[3] Kevin P. Murphy,et al. Machine learning - a probabilistic perspective , 2012, Adaptive computation and machine learning series.
[4] John Krumm,et al. Ubiquitous Computing Fundamentals , 2009 .
[5] Mo Li,et al. IODetector: a generic service for indoor outdoor detection , 2012, SenSys '12.
[6] Calvin C. Newport. Improving Wireless Network Performance Using Sensor Hints , 2011, NSDI.
[7] Philip S. Yu,et al. Transportation mode detection using mobile phones and GIS information , 2011, GIS.
[8] Haitao Wu,et al. Footprint: cellular assisted Wi-Fi AP discovery on mobile phones for energy saving , 2009, WINTECH '09.
[9] Deborah Estrin,et al. SensLoc: sensing everyday places and paths using less energy , 2010, SenSys '10.
[10] Ronald Rosenfeld,et al. Semi-supervised learning with graphs , 2005 .
[11] Mohamed N. El-Derini,et al. GAC: Energy-Efficient Hybrid GPS-Accelerometer-Compass GSM Localization , 2010, 2010 IEEE Global Telecommunications Conference GLOBECOM 2010.
[12] Sasu Tarkoma,et al. Accelerometer-based transportation mode detection on smartphones , 2013, SenSys '13.
[13] Xiaojin Zhu,et al. Introduction to Semi-Supervised Learning , 2009, Synthesis Lectures on Artificial Intelligence and Machine Learning.
[14] Moustafa Youssef,et al. No need to war-drive: unsupervised indoor localization , 2012, MobiSys '12.
[15] Venkata N. Padmanabhan,et al. Indoor localization without the pain , 2010, MobiCom.
[16] Yi Wang,et al. A framework of energy efficient mobile sensing for automatic user state recognition , 2009, MobiSys '09.
[17] David R. Karger,et al. Tackling the Poor Assumptions of Naive Bayes Text Classifiers , 2003, ICML.
[18] Romit Roy Choudhury,et al. EnLoc: Energy-Efficient Localization for Mobile Phones , 2009, IEEE INFOCOM 2009.
[19] Ramesh Govindan,et al. Energy-efficient positioning for smartphones using Cell-ID sequence matching , 2011, MobiSys '11.
[20] Anshul Rai,et al. Zee: zero-effort crowdsourcing for indoor localization , 2012, Mobicom '12.
[21] Diogo R. Ferreira,et al. Providing user context for mobile and social networking applications , 2010, Pervasive Mob. Comput..
[22] Niels Brouwers,et al. Dwelling in the canyons: Dwelling detection in urban environments using GPS, Wi-Fi, and geolocation , 2013, Pervasive Mob. Comput..
[23] Romit Roy Choudhury,et al. SurroundSense: mobile phone localization via ambience fingerprinting , 2009, MobiCom '09.
[24] Emiliano Miluzzo,et al. Pocket, Bag, Hand, etc. - Automatically Detecting Phone Context through Discovery , 2010 .
[25] Qiang Yang,et al. Tracking Mobile Users in Wireless Networks via Semi-Supervised Colocalization , 2012, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[26] Guoliang Xing,et al. PBN: towards practical activity recognition using smartphone-based body sensor networks , 2011, SenSys.
[27] Leah Epstein,et al. Tracking mobile users , 2005, Algorithms for Optimization with Incomplete Information.
[28] Jun Yang,et al. Efficient in-pocket detection with mobile phones , 2013, UbiComp.