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Mapping parallelism in a functional IR through constraint satisfaction: a case study on convolution for mobile GPUs., , , и . CC, стр. 218-230. ACM, (2022)Impact of Indoor-Outdoor Context on Crowdsourcing based Mobile Coverage Analysis., , и . AllThingsCellular@SIGCOMM, стр. 45-50. ACM, (2015)A semi-supervised learning approach for robust indoor-outdoor detection with smartphones., , , и . SenSys, стр. 280-294. ACM, (2014)HiMLoc: Indoor smartphone localization via activity aware Pedestrian Dead Reckoning with selective crowdsourced WiFi fingerprinting., и . IPIN, стр. 1-10. IEEE, (2013)Calibrating Recurrent Neural Networks on Smartphone Inertial Sensors for Location Tracking., и . IPIN, стр. 1-8. IEEE, (2019)Towards Federated Learning with Attention Transfer to Mitigate System and Data Heterogeneity of Clients., и . EdgeSys@EuroSys, стр. 61-66. ACM, (2021)Towards multimodal deep learning for activity recognition on mobile devices., , , , , и . UbiComp Adjunct, стр. 185-188. ACM, (2016)MM-Fit: Multimodal Deep Learning for Automatic Exercise Logging across Sensing Devices., , и . Proc. ACM Interact. Mob. Wearable Ubiquitous Technol., 4 (4): 168:1-168:22 (2020)CamLoc: Pedestrian Location Estimation through Body Pose Estimation on Smart Cameras., , и . IPIN, стр. 1-8. IEEE, (2019)An Immune Inspired Algorithm for Fault Tolerant Enhanced Multimodal Machine Learning., и . BIBM, стр. 2194-2200. IEEE, (2021)