Tianyi Li

Orcid: 0000-0001-5424-6442

Affiliations:
  • Aalborg University, Department of Computer Science, Denmark
  • Northeastern University, School of Computer Science and Engineering, Shenyang, China (former)


According to our database1, Tianyi Li authored at least 24 papers between 2017 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

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Online presence:

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Bibliography

2024
Estimator: An Effective and Scalable Framework for Transportation Mode Classification Over Trajectories.
IEEE Trans. Intell. Transp. Syst., November, 2024

CHGNN: A Semi-Supervised Contrastive Hypergraph Learning Network.
IEEE Trans. Knowl. Data Eng., September, 2024

A Demonstration of TENDS: Time Series Management System based on Model Selection.
Proc. VLDB Endow., August, 2024

DynaHB: A Communication-Avoiding Asynchronous Distributed Framework with Hybrid Batches for Dynamic GNN Training.
Proc. VLDB Endow., July, 2024

FedAPT: Joint Adaptive Parameter Freezing and Resource Allocation for Communication-Efficient Federated Vehicular Networks.
IEEE Internet Things J., June, 2024

Spatio-Temporal Trajectory Similarity Measures: A Comprehensive Survey and Quantitative Study.
IEEE Trans. Knowl. Data Eng., May, 2024

FedAGL: A Communication-Efficient Federated Vehicular Network.
IEEE Trans. Intell. Veh., February, 2024

UniTE: A Survey and Unified Pipeline for Pre-training ST Trajectory Embeddings.
CoRR, 2024

TSec: An Efficient and Effective Framework for Time Series Classification.
Proceedings of the 40th IEEE International Conference on Data Engineering, 2024

LTPG: Large-Batch Transaction Processing on GPUs with Deterministic Concurrency Control.
Proceedings of the 40th IEEE International Conference on Data Engineering, 2024

SWISP: Distributed Convoy Mining via Sliding Window-based Indexing and Sub-track Partitioning.
Proceedings of the 40th IEEE International Conference on Data Engineering, 2024

2023
ADGNN: Towards Scalable GNN Training with Aggregation-Difference Aware Sampling.
Proc. ACM Manag. Data, December, 2023

SimpleTS: An Efficient and Universal Model Selection Framework for Time Series Forecasting.
Proc. VLDB Endow., 2023

Real-time Workload Pattern Analysis for Large-scale Cloud Databases.
Proc. VLDB Endow., 2023

Efficient Cost Modeling of Space-filling Curves.
CoRR, 2023

Unsupervised Entity Alignment for Temporal Knowledge Graphs.
Proceedings of the ACM Web Conference 2023, 2023

SEA: A Scalable Entity Alignment System.
Proceedings of the 46th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2023

2022
Distributed Resilient Double-Gradient-Descent Based Energy Management Strategy for Multi-Energy System Under DoS Attacks.
IEEE Trans. Netw. Sci. Eng., 2022

ClusterEA: Scalable Entity Alignment with Stochastic Training and Normalized Mini-batch Similarities.
Proceedings of the KDD '22: The 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Washington, DC, USA, August 14, 2022

Evolutionary Clustering of Moving Objects.
Proceedings of the 38th IEEE International Conference on Data Engineering, 2022

2021
TRACE: Real-time Compression of Streaming Trajectories in Road Networks.
Proc. VLDB Endow., 2021

Evolutionary Clustering of Streaming Trajectories.
CoRR, 2021

2020
Compression of Uncertain Trajectories in Road Networks.
Proc. VLDB Endow., 2020

2017
An Effective and Efficient Truth Discovery Framework over Data Streams.
Proceedings of the 20th International Conference on Extending Database Technology, 2017


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