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What this work says
Outgoing claims: the papers this work cites, builds on, or argues with.
inferredcites →https://doi.org/10.1002/9780470567371.ch1openalex-snapshot
Introduction to Bayesian Statistics
inferredcites →https://doi.org/10.1007/978-1-4614-7138-7openalex-snapshot
An Introduction to Statistical Learning
inferredcites →https://doi.org/10.1007/978-3-031-38747-0openalex-snapshot
An Introduction to Statistical Learning
inferredcites →https://doi.org/10.1007/978-3-642-12654-3_9openalex-snapshot
Recruitment Framework for Participatory Sensing Data Collections
inferredcites →https://doi.org/10.1007/s10208-009-9045-5openalex-snapshot
Exact Matrix Completion via Convex Optimization
inferredcites →https://doi.org/10.1007/s10661-005-9022-7openalex-snapshot
Air Pollution Concentrations of PM2.5, PM10 and NO2 at Ambient and Kerbsite and Their Correlation in Metro City – Mumbai
inferredcites →https://doi.org/10.1016/j.pmcj.2010.08.006openalex-snapshot
Dynamic pricing incentive for participatory sensing
inferredcites →https://doi.org/10.1016/s0168-1923(98)00076-8openalex-snapshot
Measured and predicted air temperatures at basin to regional scales in the southern Appalachian mountains
inferredcites →https://doi.org/10.1098/rspa.1946.0056openalex-snapshot
An invariant form for the prior probability in estimation problems
inferredcites →https://doi.org/10.1109/comst.2015.2415528openalex-snapshot
Incentives for Mobile Crowd Sensing: A Survey
inferredcites →https://doi.org/10.1109/icassp.2010.5495305openalex-snapshot
Nonnegative matrix partial co-factorization for drum source separation
inferredcites →https://doi.org/10.1109/infcom.2012.6195568openalex-snapshot
Energy-efficient collaborative sensing with mobile phones
inferredcites →https://doi.org/10.1109/infocom.2014.6848001openalex-snapshot
Toward optimal allocation of location dependent tasks in crowdsensing
inferredcites →https://doi.org/10.1109/ipsn.2014.6846756openalex-snapshot
Face recognition on smartphones via optimised Sparse Representation Classification
inferredcites →https://doi.org/10.1109/iri.2011.6009563openalex-snapshot
Non-myopic active learning for recommender systems based on Matrix Factorization
inferredcites →https://doi.org/10.1109/jiot.2016.2608141openalex-snapshot
Fine-Grained Multitask Allocation for Participatory Sensing With a Shared Budget
inferredcites →https://doi.org/10.1109/mcom.2011.6069707openalex-snapshot
Mobile crowdsensing: current state and future challenges
inferredcites →https://doi.org/10.1109/mcom.2014.6871668openalex-snapshot
4W1H in mobile crowd sensing
inferredcites →https://doi.org/10.1109/mcom.2016.7509395openalex-snapshot
Sparse mobile crowdsensing: challenges and opportunities
inferredcites →https://doi.org/10.1109/percom.2012.6199855openalex-snapshot
A location-based incentive mechanism for participatory sensing systems with budget constraints
inferredcites →https://doi.org/10.1109/percom.2013.6526723openalex-snapshot
Probabilistic registration for large-scale mobile participatory sensing
inferredcites →https://doi.org/10.1109/sahcn.2011.5984884openalex-snapshot
Distance and time based node selection for probabilistic coverage in People-Centric Sensing
inferredcites →https://doi.org/10.1109/thms.2016.2599489openalex-snapshot
ActiveCrowd: A Framework for Optimized Multitask Allocation in Mobile Crowdsensing Systems
inferredcites →https://doi.org/10.1109/tit.1967.1053964openalex-snapshot
Nearest neighbor pattern classification
inferredcites →https://doi.org/10.1109/tmc.2012.205openalex-snapshot
A Compressive Sensing Approach to Urban Traffic Estimation with Probe Vehicles
inferredcites →https://doi.org/10.1109/tmc.2014.2357791openalex-snapshot
EMC3: Energy-efficient data transfer in mobile crowdsensing under full coverage constraint
inferredcites →https://doi.org/10.1109/tmc.2015.2483505openalex-snapshot
iCrowd: Near-Optimal Task Allocation for Piggyback Crowdsensing
inferredcites →https://doi.org/10.1109/tpds.2013.269openalex-snapshot
Data Loss and Reconstruction in Wireless Sensor Networks
inferredcites →https://doi.org/10.1109/twc.2012.081612.110612openalex-snapshot
Sensing, Compression, and Recovery for WSNs: Sparse Signal Modeling and Monitoring Framework
inferredcites →https://doi.org/10.1137/070697835openalex-snapshot
Guaranteed Minimum-Rank Solutions of Linear Matrix Equations via Nuclear Norm Minimization
inferredcites →https://doi.org/10.1145/1401890.1401969openalex-snapshot
Relational learning via collective matrix factorization
inferredcites →https://doi.org/10.1145/1592568.1592600openalex-snapshot
Spatio-temporal compressive sensing and internet traffic matrices
inferredcites →https://doi.org/10.1145/1594977.1592600openalex-snapshot
Spatio-temporal compressive sensing and internet traffic matrices
inferredcites →https://doi.org/10.1145/1864349.1864355openalex-snapshot
Examining micro-payments for participatory sensing data collections
inferredcites →https://doi.org/10.1145/2487575.2487627openalex-snapshot
Active learning and search on low-rank matrices
inferredcites →https://doi.org/10.1145/2493432.2493498openalex-snapshot
Understanding the coverage and scalability of place-centric crowdsensing
inferredcites →https://doi.org/10.1145/2505821.2505834openalex-snapshot
Real-time air quality monitoring through mobile sensing in metropolitan areas
inferredcites →https://doi.org/10.1145/2623330.2623653openalex-snapshot
Inferring gas consumption and pollution emission of vehicles throughout a city
inferredcites →https://doi.org/10.1145/2632048.2632102openalex-snapshot
Diagnosing New York city's noises with ubiquitous data
inferredcites →https://doi.org/10.1145/2737095.2737105openalex-snapshot
Cost-aware compressive sensing for networked sensing systems
inferredcites →https://doi.org/10.1175/1520-0442(2001)014<0853:aoicde>2.0.co;2openalex-snapshot
Analysis of Incomplete Climate Data: Estimation of Mean Values and Covariance Matrices and Imputation of Missing Values
inferredcites →https://doi.org/10.1201/9780429246593openalex-snapshot
An Introduction to the Bootstrap
inferredcites →https://doi.org/10.1609/aaai.v30i1.10291openalex-snapshot
Multi-Domain Active Learning for Recommendation
inferredcites →https://doi.org/10.5194/npg-13-151-2006openalex-snapshot
Spatio-temporal filling of missing points in geophysical data sets
inferredcites →https://doi.org/10.5591/978-1-57735-516-8/ijcai11-386openalex-snapshot
Transfer learning to predict missing ratings via heterogeneous user feedbacks
What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
inferred← citeshttps://doi.org/10.1007/978-3-031-72732-0_7openalex-snapshot
Deep Data Inference on Sparse Mobile Crowdsensing
inferred← citeshttps://doi.org/10.1007/978-981-99-2385-4_11openalex-snapshot
Research on Cost Control of Mobile Crowdsourcing Supporting Low Budget in Large Scale Environmental Information Monitoring
inferred← citeshttps://doi.org/10.1007/s11227-022-04518-zopenalex-snapshot
Task reduction using regression-based missing data imputation in sparse mobile crowdsensing
inferred← citeshttps://doi.org/10.1007/s11270-023-06127-9openalex-snapshot
Data Quality in IoT-Based Air Quality Monitoring Systems: a Systematic Mapping Study
inferred← citeshttps://doi.org/10.1007/s11704-019-9034-zopenalex-snapshot
Understanding urban structures and crowd dynamics leveraging large-scale vehicle mobility data
inferred← citeshttps://doi.org/10.1007/s42486-025-00202-2openalex-snapshot
MBBALD: an active data acquisition strategy via sparse mobile crowdsensing for embodied AI
inferred← citeshttps://doi.org/10.1016/j.comnet.2019.06.010openalex-snapshot
Reinforcement learning-based cell selection in sparse mobile crowdsensing
inferred← citeshttps://doi.org/10.1016/j.future.2019.02.014openalex-snapshot
Mobile crowdsensing: A survey on privacy-preservation, task management, assignment models, and incentives mechanisms
inferred← citeshttps://doi.org/10.1016/j.future.2024.04.018openalex-snapshot
Region-based compressive distributed storage in Mobile CrowdSensing
inferred← citeshttps://doi.org/10.1016/j.ins.2019.02.011openalex-snapshot
Privacy-preserving task recommendation with win-win incentives for mobile crowdsourcing
inferred← citeshttps://doi.org/10.1016/j.ins.2023.119361openalex-snapshot
Three-way decision based participants selection optimization model in sparse mobile crowdsensing
inferred← citeshttps://doi.org/10.1016/j.ins.2024.120274openalex-snapshot
LC-TDC: A low cost and truth data collection scheme by using missing data imputation in sparse mobile crowdsensing
inferred← citeshttps://doi.org/10.1016/j.jnlssr.2021.08.004openalex-snapshot
Multi-sensing paradigm based urban air quality monitoring and hazardous gas source analyzing: a review
inferred← citeshttps://doi.org/10.1016/j.pmcj.2018.06.001openalex-snapshot
An efficient method for physical fields mapping through crowdsensing
inferred← citeshttps://doi.org/10.1016/j.pmcj.2020.101181openalex-snapshot
The active learning multi-task allocation method in mobile crowd sensing based on normal cloud model
inferred← citeshttps://doi.org/10.1038/s41598-025-88305-9openalex-snapshot
Real time task planning for order picking in intelligent logistics warehousing
inferred← citeshttps://doi.org/10.1080/0951192x.2025.2545494openalex-snapshot
Building resilient digital twin with digital cousins: a method for accurate prediction from multi-source fusion in manufacturing
inferred← citeshttps://doi.org/10.1109/access.2018.2870298openalex-snapshot
EdgeSense: Edge-Mediated Spatial- Temporal Crowdsensing
inferred← citeshttps://doi.org/10.1109/access.2019.2924184openalex-snapshot
Multi-Dimensional Urban Sensing in Sparse Mobile Crowdsensing
inferred← citeshttps://doi.org/10.1109/cac.2018.8623650openalex-snapshot
Heterogeneous Self-Organizing Map for Multi-type Tasks Allocation with Multirobot in Different Task Modes
inferred← citeshttps://doi.org/10.1109/comst.2019.2914030openalex-snapshot
A Survey on Mobile Crowdsensing Systems: Challenges, Solutions, and Opportunities
inferred← citeshttps://doi.org/10.1109/comst.2021.3073036openalex-snapshot
Deep Reinforcement Learning for Internet of Things: A Comprehensive Survey
inferred← citeshttps://doi.org/10.1109/icdcs.2018.00164openalex-snapshot
Cell Selection with Deep Reinforcement Learning in Sparse Mobile Crowdsensing
inferred← citeshttps://doi.org/10.1109/icdcs54860.2022.00077openalex-snapshot
CODE: Compact IoT Data Collection with Precise Matrix Sampling and Efficient Inference
inferred← citeshttps://doi.org/10.1109/infocom48880.2022.9796868openalex-snapshot
Spatiotemporal Fracture Data Inference in Sparse Urban CrowdSensing
inferred← citeshttps://doi.org/10.1109/infocom52122.2024.10621156openalex-snapshot
Few-Shot Data Completion for New Tasks in Sparse Crowdsensing
inferred← citeshttps://doi.org/10.1109/infocom53939.2023.10228982openalex-snapshot
Spatiotemporal Transformer for Data Inference and Long Prediction in Sparse Mobile CrowdSensing
inferred← citeshttps://doi.org/10.1109/iwqos52092.2021.9521275openalex-snapshot
Exploiting Outlier Value Effects in Sparse Urban CrowdSensing
inferred← citeshttps://doi.org/10.1109/iwqos57198.2023.10188803openalex-snapshot
Data-Driven Similarity-based Worker Recruitment Towards Multi-task Data Inference for Sparse Mobile Crowdsensing
inferred← citeshttps://doi.org/10.1109/jiot.2018.2864341openalex-snapshot
Task Allocation in Mobile Crowd Sensing: State-of-the-Art and Future Opportunities
inferred← citeshttps://doi.org/10.1109/jiot.2018.2875520openalex-snapshot
Folo: Latency and Quality Optimized Task Allocation in Vehicular Fog Computing
inferred← citeshttps://doi.org/10.1109/jiot.2019.2901093openalex-snapshot
CrowdTracking: Real-Time Vehicle Tracking Through Mobile Crowdsensing
inferred← citeshttps://doi.org/10.1109/jiot.2019.2909296openalex-snapshot
UniTask: A Unified Task Assignment Design for Mobile Crowdsourcing-Based Urban Sensing
inferred← citeshttps://doi.org/10.1109/jiot.2019.2957399openalex-snapshot
User Recruitment for Enhancing Data Inference Accuracy in Sparse Mobile Crowdsensing
inferred← citeshttps://doi.org/10.1109/jiot.2020.3024833openalex-snapshot
A Cost-Quality Beneficial Cell Selection Approach for Sparse Mobile Crowdsensing With Diverse Sensing Costs
inferred← citeshttps://doi.org/10.1109/jiot.2021.3060815openalex-snapshot
Cost-Effective Active Sparse Urban Sensing: Adversarial Autoencoder Approach
inferred← citeshttps://doi.org/10.1109/jiot.2021.3068415openalex-snapshot
Keeping Cell Selection Model Up-to-Date to Adapt to Time-Dependent Environment in Sparse Mobile Crowdsensing
inferred← citeshttps://doi.org/10.1109/jiot.2022.3198081openalex-snapshot
Multi-View Matrix Factorization for Sparse Mobile Crowdsensing
inferred← citeshttps://doi.org/10.1109/jiot.2023.3318817openalex-snapshot
Online User Recruitment With Adaptive Budget Segmentation in Sparse Mobile Crowdsensing
inferred← citeshttps://doi.org/10.1109/jiot.2024.3356554openalex-snapshot
Sparse Mobile Crowdsensing for Cost-Effective Traffic State Estimation With Spatio–Temporal Transformer Graph Neural Network
inferred← citeshttps://doi.org/10.1109/jiot.2024.3414496openalex-snapshot
Sparse Mobile Crowdsensing for Gas Monitoring in Coal Mine Working Face
inferred← citeshttps://doi.org/10.1109/jiot.2025.3540501openalex-snapshot
Task Assignment Scheme Designed for Online Urban Sensing Based on Sparse Mobile Crowdsensing
inferred← citeshttps://doi.org/10.1109/jiot.2025.3566314openalex-snapshot
Demand-Driven Sparse Mobile Crowdsensing With Neighborhood-Aware Reconstruction
inferred← citeshttps://doi.org/10.1109/jiot.2025.3586595openalex-snapshot
Adaptive Role Learning With Evolutionary Multiagent Reinforcement Learning for UAV-Vehicle Collaboration in Sparse Mobile Crowdsensing
inferred← citeshttps://doi.org/10.1109/jsen.2022.3154591openalex-snapshot
A Training-Free Multipath Enhancement (TFME-RTI) Method for Device-Free Multi-Target Localization
inferred← citeshttps://doi.org/10.1109/mass50613.2020.00041openalex-snapshot
Fine-grained Urban Prediction via Sparse Mobile CrowdSensing
inferred← citeshttps://doi.org/10.1109/mc.2018.2879994openalex-snapshot
Hybrid Vehicular Crowdsourcing With Driverless Cars: Challenges and a Solution
inferred← citeshttps://doi.org/10.1109/mc.2020.3023931openalex-snapshot
Crowd-Machine Hybrid Urban Sensing and Computing
inferred← citeshttps://doi.org/10.1109/msn63567.2024.00132openalex-snapshot
Multi-Task Assignment in Sparse Crowdsensing Using Intra-Task and Inter-Task Data Correlations
inferred← citeshttps://doi.org/10.1109/ojcs.2022.3177290openalex-snapshot
A Survey of Sparse Mobile Crowdsensing: Developments and Opportunities
inferred← citeshttps://doi.org/10.1109/tetc.2020.3045463openalex-snapshot
SDLSC-TA: Subarea Division Learning Based Task Allocation in Sparse Mobile Crowdsensing
inferred← citeshttps://doi.org/10.1109/tifs.2020.2975925openalex-snapshot
Sparse Mobile Crowdsensing With Differential and Distortion Location Privacy
inferred← citeshttps://doi.org/10.1109/tii.2018.2868703openalex-snapshot
Learning-Assisted Optimization in Mobile Crowd Sensing: A Survey
inferred← citeshttps://doi.org/10.1109/tii.2020.3028616openalex-snapshot
Deep Learning-Enabled Sparse Industrial Crowdsensing and Prediction
inferred← citeshttps://doi.org/10.1109/tiv.2022.3216318openalex-snapshot
A Crowd-Aided Vehicular Hybrid Sensing Framework for Intelligent Transportation Systems
inferred← citeshttps://doi.org/10.1109/tmc.2018.2861864openalex-snapshot
FooDNet: Toward an Optimized Food Delivery Network Based on Spatial Crowdsourcing
inferred← citeshttps://doi.org/10.1109/tmc.2018.2879098openalex-snapshot
A Prediction-Based User Selection Framework for Heterogeneous Mobile CrowdSensing
inferred← citeshttps://doi.org/10.1109/tmc.2019.2953911openalex-snapshot
Cost-Efficient Mobile Crowdsensing With Spatial-Temporal Awareness
inferred← citeshttps://doi.org/10.1109/tmc.2020.2983688openalex-snapshot
Profit-Oriented Task Allocation for Mobile Crowdsensing With Worker Dynamics: Cooperative Offline Solution and Predictive Online Solution
inferred← citeshttps://doi.org/10.1109/tmc.2022.3178885openalex-snapshot
AFCS: Aggregation-Free Spatial-Temporal Mobile Community Sensing
inferred← citeshttps://doi.org/10.1109/tmc.2022.3195706openalex-snapshot
Spatiotemporal Urban Inference and Prediction in Sparse Mobile CrowdSensing: a Graph Neural Network Approach
inferred← citeshttps://doi.org/10.1109/tmc.2023.3315232openalex-snapshot
Co-Optimization of Cell Selection and Data Offloading in Sparse Mobile Crowdsensing
inferred← citeshttps://doi.org/10.1109/tmc.2023.3331429openalex-snapshot
A Data-Driven Crowdsensing Framework for Parking Violation Detection
inferred← citeshttps://doi.org/10.1109/tmc.2023.3339089openalex-snapshot
Large-Scale Spatiotemporal Fracture Data Completion in Sparse CrowdSensing
inferred← citeshttps://doi.org/10.1109/tmc.2023.3342206openalex-snapshot
Adaptive Budgeting for Collaborative Multi-Task Data Collection in Online Sparse Crowdsensing
inferred← citeshttps://doi.org/10.1109/tmc.2024.3480983openalex-snapshot
A New Data Completion Perspective on Sparse CrowdSensing: Spatiotemporal Evolutionary Inference Approach
inferred← citeshttps://doi.org/10.1109/tmc.2026.3678980openalex-snapshot
MapT-STC: A One-Shot Spatiotemporal Data Completion Framework for Cold-Start Tasks in Sparse Crowdsensing
inferred← citeshttps://doi.org/10.1109/tmc.2026.3697838openalex-snapshot
ST-CoSense: Spatio-Temporal Cooperative Sensing for Resource-Constrained Urban Applications
inferred← citeshttps://doi.org/10.1109/tmc.2026.3715232openalex-snapshot
Asynchronous Multi-Agent Reinforcement Learning for Collaborative UAV Sensing in Sparse Mobile Crowdsensing
inferred← citeshttps://doi.org/10.1109/tnet.2022.3201545openalex-snapshot
Outlier-Concerned Data Completion Exploiting Intra- and Inter-Data Correlations in Sparse CrowdSensing
inferred← citeshttps://doi.org/10.1109/tnet.2023.3323522openalex-snapshot
Spatiotemporal Fracture Data Inference in Sparse Mobile Crowdsensing: A Graph- and Attention-Based Approach
inferred← citeshttps://doi.org/10.1109/tnet.2024.3397309openalex-snapshot
Robust Data Inference and Cost-Effective Cell Selection for Sparse Mobile Crowdsensing
inferred← citeshttps://doi.org/10.1109/tnsm.2025.3597953openalex-snapshot
Sensify: A Learning-Based Budget-Aware Task Assignment in Mobile Crowdsensing
inferred← citeshttps://doi.org/10.1109/tpds.2022.3213259openalex-snapshot
Tripartite Graph Aided Tensor Completion For Sparse Network Measurement
inferred← citeshttps://doi.org/10.1109/tpds.2024.3453607openalex-snapshot
CODE+: Fast and Accurate Inference for Compact Distributed IoT Data Collection
inferred← citeshttps://doi.org/10.1109/tsc.2026.3664086openalex-snapshot
Data Pricing via Uncertainty Quantification for Sparse Mobile CrowdSensing
inferred← citeshttps://doi.org/10.1109/tvt.2021.3077112openalex-snapshot
Trustworthy and Cost-Effective Cell Selection for Sparse Mobile Crowdsensing Systems
inferred← citeshttps://doi.org/10.1145/3299869.3319856openalex-snapshot
Active Sparse Mobile Crowd Sensing Based on Matrix Completion
inferred← citeshttps://doi.org/10.1145/3326164openalex-snapshot
Efficient User Guidance for Validating Participatory Sensing Data
inferred← citeshttps://doi.org/10.1145/3342515openalex-snapshot
Towards Profit Optimization During Online Participant Selection in Compressive Mobile Crowdsensing
inferred← citeshttps://doi.org/10.1145/3442698openalex-snapshot
Task Planning Considering Location Familiarity in Spatial Crowdsourcing
inferred← citeshttps://doi.org/10.1145/3498321openalex-snapshot
Compressive Sensing Based Distributed Data Storage for Mobile Crowdsensing
inferred← citeshttps://doi.org/10.1145/3838457.3838471openalex-snapshot
O-SPTM: Online Shared-Private Tensor Modeling for Adaptive Active Multi-Task Sparse Mobile Crowdsensing
inferred← citeshttps://doi.org/10.14209/jcis.2019.26openalex-snapshot
Credibility on Crowdsensing Data Acquisition
inferred← citeshttps://doi.org/10.48550/arxiv.2011.03208openalex-snapshot
Federated Crowdsensing: Framework and Challenges
inferred← citeshttps://doi.org/10.55041/ijsrem26089openalex-snapshot
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