Shintaro Fukushima

Orcid: 0000-0002-8788-5555

According to our database1, Shintaro Fukushima authored at least 24 papers between 2018 and 2026.

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

Timeline

Legend:

Book  In proceedings  Article  PhD thesis  Dataset  Other 

Links

Online presence:

On csauthors.net:

Bibliography

2026
Localization-Guided Foreground Augmentation in Autonomous Driving.
CoRR, April, 2026

TrajGPT-R: Generating Urban Mobility Trajectory with Reinforcement Learning-Enhanced Generative Pre-trained Transformer.
CoRR, February, 2026

Towards Resilient Transportation: A Conditional Transformer for Accident-Informed Traffic Forecasting.
Proceedings of the 32nd ACM SIGKDD Conference on Knowledge Discovery and Data Mining V.1, 2026

2025
Maintaining Orientation of a Local Neighborhood in High-dimensional Space for Real-time Visualization of Massive Data.
J. Inf. Process., 2025

Popularity‑Bias Vulnerability: Semi‑Supervised Label Inference Attack on Federated Recommender Systems.
Proceedings of the Nineteenth ACM Conference on Recommender Systems, 2025

How Different from the Past? Spatio-Temporal Time Series Forecasting with Self-Supervised Deviation Learning.
Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2025, 2025

2024
Multimodal Point-of-Interest Recommendation.
CoRR, 2024

Leveraging trajectory simplification for efficient map-matching on road network.
Proceedings of the 25th IEEE International Conference on Mobile Data Management, 2024

Empirical Data-Driven Approach to Eco-Friendly Deceleration.
Proceedings of the 27th IEEE International Conference on Intelligent Transportation Systems, 2024

A Convenient Approach for Lane-Level Congestion Detection with On-Board Camera Images and Vehicle Data.
Proceedings of the 27th IEEE International Conference on Intelligent Transportation Systems, 2024

Network-Wide Traffic Volume Estimation Using Joint Matrix Factorization with Traffic Flow Conservation Law.
Proceedings of the 27th IEEE International Conference on Intelligent Transportation Systems, 2024

Estimating Reduction in Travel Time Based on Large Scale Driving Data from Connected Vehicles.
Proceedings of the 27th IEEE International Conference on Intelligent Transportation Systems, 2024

Graph Community Augmentation with GMM-Based Modeling in Latent Space.
Proceedings of the IEEE International Conference on Data Mining, 2024

2023
Finding Energy-Efficient and Fast Detour Routes in Unusual Traffic Events.
Proceedings of the 26th IEEE International Conference on Intelligent Transportation Systems, 2023

Balancing Summarization and Change Detection in Graph Streams.
Proceedings of the IEEE International Conference on Data Mining, 2023

Revisiting Mobility Modeling with Graph: A Graph Transformer Model for Next Point-of-Interest Recommendation.
Proceedings of the 31st ACM International Conference on Advances in Geographic Information Systems, 2023

Spatio-Temporal Meta-Graph Learning for Traffic Forecasting.
Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2022
Estimating Total Traffic Volume with Statistical Modeling Approach.
Proceedings of the 25th IEEE International Conference on Intelligent Transportation Systems, 2022

2021
Graph Summarization with Latent Variable Probabilistic Models.
Proceedings of the Complex Networks & Their Applications X - Volume 2, Proceedings of the Tenth International Conference on Complex Networks and Their Applications COMPLEX NETWORKS 2021, Madrid, Spain, November 30, 2021

2020
Change Sign Detection with Differential MDL Change Statistics and its Applications to COVID-19 Pandemic Analysis.
CoRR, 2020

Online Robust and Adaptive Learning from Data Streams.
CoRR, 2020

Detecting Hierarchical Changes in Latent Variable Models.
Proceedings of the 20th IEEE International Conference on Data Mining, 2020

2019
Detecting Metachanges in Data Streams from the Viewpoint of the MDL Principle.
Entropy, 2019

2018
Model Change Detection With the MDL Principle.
IEEE Trans. Inf. Theory, 2018


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