2025
AimTS: Augmented Series and Image Contrastive Learning for Time Series Classification.
CoRR, April, 2025
Mantis: Lightweight Calibrated Foundation Model for User-Friendly Time Series Classification.
CoRR, February, 2025
Air Quality Prediction with Physics-Guided Dual Neural ODEs in Open Systems.
Proceedings of the Thirteenth International Conference on Learning Representations, 2025
Towards a General Time Series Anomaly Detector with Adaptive Bottlenecks and Dual Adversarial Decoders.
Proceedings of the Thirteenth International Conference on Learning Representations, 2025
2024
Label-Aware Distribution Calibration for Long-Tailed Classification.
IEEE Trans. Neural Networks Learn. Syst., May, 2024
Air Quality Prediction with Physics-Informed Dual Neural ODEs in Open Systems.
CoRR, 2024
ROSE: Register Assisted General Time Series Forecasting with Decomposed Frequency Learning.
CoRR, 2024
Enhancing Multivariate Time Series Forecasting with Mutual Information-driven Cross-Variable and Temporal Modeling.
CoRR, 2024
SEFraud: Graph-based Self-Explainable Fraud Detection via Interpretative Mask Learning.
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Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2024
DWLR: Domain Adaptation under Label Shift for Wearable Sensor.
Proceedings of the Thirty-Third International Joint Conference on Artificial Intelligence, 2024
Disentangling Domain and General Representations for Time Series Classification.
Proceedings of the Thirty-Third International Joint Conference on Artificial Intelligence, 2024
2023
A Shapelet-based Framework for Unsupervised Multivariate Time Series Representation Learning.
Proc. VLDB Endow., November, 2023
Contrastive Shapelet Learning for Unsupervised Multivariate Time Series Representation Learning.
CoRR, 2023
MTS-Mixers: Multivariate Time Series Forecasting via Factorized Temporal and Channel Mixing.
CoRR, 2023
Ti-MAE: Self-Supervised Masked Time Series Autoencoders.
CoRR, 2023
κHGCN: Tree-likeness Modeling via Continuous and Discrete Curvature Learning.
Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2023
SMARTformer: Semi-Autoregressive Transformer with Efficient Integrated Window Attention for Long Time Series Forecasting.
Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence, 2023
Mitigating Semantic Confusion from Hostile Neighborhood for Graph Active Learning.
Proceedings of the 32nd ACM International Conference on Information and Knowledge Management, 2023
MATA*: Combining Learnable Node Matching with A* Algorithm for Approximate Graph Edit Distance Computation.
Proceedings of the 32nd ACM International Conference on Information and Knowledge Management, 2023
Inducing Neural Collapse in Deep Long-tailed Learning.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023
Generative Oversampling for Imbalanced Data via Majority-Guided VAE.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023
2022
LDAAD: An effective label de-noising approach for anomaly detection.
J. Intell. Fuzzy Syst., 2022
Hyperbolic Curvature Graph Neural Network.
CoRR, 2022
Hyperbolic Graph Representation Learning: A Tutorial.
CoRR, 2022
TeleGraph: A Benchmark Dataset for Hierarchical Link Prediction.
CoRR, 2022
Hyperbolic Graph Neural Networks: A Review of Methods and Applications.
CoRR, 2022
Discovering Representative Attribute-stars via Minimum Description Length.
Proceedings of the 38th IEEE International Conference on Data Engineering, 2022
Leveraging Only the Category Name for Aspect Detection through Prompt-based Constrained Clustering.
Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2022, 2022
Contrastive Representation based Active Learning for Time Series.
Proceedings of the IEEE Intl. Conf. on Dependable, 2022
2021
gCastle: A Python Toolbox for Causal Discovery.
CoRR, 2021
An Ensemble Noise-Robust K-fold Cross-Validation Selection Method for Noisy Labels.
CoRR, 2021
Mask-GVAE: Blind Denoising Graphs via Partition.
Proceedings of the WWW '21: The Web Conference 2021, 2021
Learning from Noisy Labels with Complementary Loss Functions.
Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021
2020
Spatio-Temporal Hybrid Graph Convolutional Network for Traffic Forecasting in Telecommunication Networks.
CoRR, 2020
Proactive microwave link anomaly detection in cellular data networks.
Comput. Networks, 2020
2019
Predicting Path Failure In Time-Evolving Graphs.
Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2019
2018
CellPAD: Detecting Performance Anomalies in Cellular Networks via Regression Analysis.
Proceedings of the 2018 IFIP Networking Conference and Workshops, 2018
2017
An Intelligent Customer Care Assistant System for Large-Scale Cellular Network Diagnosis.
Proceedings of the 23rd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, Halifax, NS, Canada, August 13, 2017
2016
SAND: A fault-tolerant streaming architecture for network traffic analytics.
J. Syst. Softw., 2016
2015
An In-depth Analysis of 3G Traffic and Performance.
Proceedings of the 5th Workshop on All Things Cellular: Operations, 2015
2013
NIM: Scalable Distributed Stream Process System on Mobile Network Data.
Proceedings of the 13th IEEE International Conference on Data Mining Workshops, 2013
2012
A Panoramic View of 3G Data/Control-Plane Traffic: Mobile Device Perspective.
Proceedings of the NETWORKING 2012, 2012