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08/23/2023
A Survey for Federated Learning Evaluations: Goals and Measures
Evaluation is a systematic approach to assessing how well a system achie...
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08/17/2023
Knowledge-inspired Subdomain Adaptation for Cross-Domain Knowledge Transfer
Most state-of-the-art deep domain adaptation techniques align source and...
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06/07/2023
UCTB: An Urban Computing Tool Box for Spatiotemporal Crowd Flow Prediction
Spatiotemporal crowd flow prediction is one of the key technologies in s...
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06/05/2023
A Data-driven Region Generation Framework for Spatiotemporal Transportation Service Management
MAUP (modifiable areal unit problem) is a fundamental problem for spatia...
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04/04/2023
A Survey on Vertical Federated Learning: From a Layered Perspective
Vertical federated learning (VFL) is a promising category of federated l...
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02/11/2023
Cross-center Early Sepsis Recognition by Medical Knowledge Guided Collaborative Learning for Data-scarce Hospitals
There are significant regional inequities in health resources around the...
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02/11/2023
Vertical Federated Knowledge Transfer via Representation Distillation for Healthcare Collaboration Networks
Collaboration between healthcare institutions can significantly lessen t...
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12/10/2022
A Unified Knowledge Graph Service for Developing Domain Language Models in AI Software
Natural Language Processing (NLP) is one of the core techniques in AI so...
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06/28/2022
Secure Forward Aggregation for Vertical Federated Neural Networks
Vertical federated learning (VFL) is attracting much attention because i...
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05/28/2022
Large-Scale Privacy-Preserving Network Embedding against Private Link Inference Attacks
Network embedding represents network nodes by a low-dimensional informat...
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04/11/2022
The Principle of Least Sensing: A Privacy-Friendly Sensing Paradigm for Urban Big Data Analytics
With the worldwide emergence of data protection regulations, how to cond...
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12/15/2021
Data Valuation for Vertical Federated Learning: An Information-Theoretic Approach
Federated learning (FL) is a promising machine learning paradigm that en...
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06/30/2021
Exploring Context Modeling Techniques on the Spatiotemporal Crowd Flow Prediction
In the big data and AI era, context is widely exploited as extra informa...
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06/30/2021
CityNet: A Multi-city Multi-modal Dataset for Smart City Applications
Data-driven approaches have been applied to many problems in urban compu...
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06/18/2021
Semi-supervised Optimal Transport with Self-paced Ensemble for Cross-hospital Sepsis Early Detection
The utilization of computer technology to solve problems in medical scen...
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05/19/2021
Federated Singular Vector Decomposition
With the promulgation of data protection laws (e.g., GDPR in 2018), priv...
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11/19/2020
FedEval: A Benchmark System with a Comprehensive Evaluation Model for Federated Learning
As an innovative solution for privacy-preserving machine learning (ML), ...
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11/06/2020
Federated Crowdsensing: Framework and Challenges
Crowdsensing is a promising sensing paradigm for smart city applications...
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09/20/2020
Exploring the Generalizability of Spatio-Temporal Crowd Flow Prediction: Meta-Modeling and an Analytic Framework
The Spatio-Temporal Crowd Flow Prediction (STCFP) problem is a classical...
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10/19/2019
CreditPrint: Credit Investigation via Geographic Footprints by Deep Learning
Credit investigation is critical for financial services. Whereas, tradit...
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06/12/2019
Secure Federated Matrix Factorization
To protect user privacy and meet law regulations, federated (machine) le...
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11/01/2018
Multi-Label Robust Factorization Autoencoder and its Application in Predicting Drug-Drug Interactions
Drug-drug interactions (DDIs) are a major cause of preventable hospitali...
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08/05/2018
Smart City Development with Urban Transfer Learning
The rapid development of big data techniques has offered great opportuni...
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07/28/2018
Bike Flow Prediction with Multi-Graph Convolutional Networks
One fundamental issue in managing bike sharing systems is the bike flow ...
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05/22/2018
Social-Network-Assisted Worker Recruitment in Mobile Crowd Sensing
Worker recruitment is a crucial research problem in Mobile Crowd Sensing...
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05/22/2018
HyTasker: Hybrid Task Allocation in Mobile Crowd Sensing
Task allocation is a major challenge in Mobile Crowd Sensing (MCS). Whil...
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05/22/2018
Task Allocation in Mobile Crowd Sensing: State of the Art and Future Opportunities
Mobile Crowd Sensing (MCS) is the special case of crowdsourcing, which l...
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04/19/2018
Cell Selection with Deep Reinforcement Learning in Sparse Mobile Crowdsensing
Sparse Mobile CrowdSensing (MCS) is a novel MCS paradigm where data infe...
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02/01/2018
Crowd Flow Prediction by Deep Spatio-Temporal Transfer Learning
Crowd flow prediction is a fundamental urban computing problem. Recently...
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10/28/2017
Geographic Differential Privacy for Mobile Crowd Coverage Maximization
For real-world mobile applications such as location-based advertising an...
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05/23/2017
