Towards Learning Disentangled Representations for Time Series
Published in ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2022
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Publications
RES: An Interpretaable Replicability Estimation System for Research Articles
Published in AAAI Conference on Artificial Intelligence (AAAI), 2022
Automated Outlier Detection via Curiosity-guided Search and Self-imitation Learning
Published in IEEE Transactions on Neural Networks and Learning Systems, 2021
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AutoOD: Neural Architecture Search for Outlier Detection
Published in IEEE International Conference on Data Engineering (ICDE), 2021
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Mitigating Gender Bias in Captioning Systems
Published in International World Wide Web Conference (WWW), 2021
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PyODDS: An End-to-end Outlier Detection System with Automated Machine Learning
Published in International World Wide Web Conference (WWW), 2020
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Towards Deeper Graph Neural Networks with Differentiable Group Normalization
Published in Conference on Neural Information Processing Systems (NeurIPS), 2020
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Dual Policy Distillation
Published in International Joint Conference on Artificial Intelligence (IJCAI), 2020
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Locality Aware Autoencoder for Manipulated Forgery Detection
Published in ACM International Conference on Information and Knowledge Management (CIKM), 2020
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Spectral Autoencoder for Anomaly Detection in Attributed Networks
Published in ACM International Conference on Information and Knowledge Management (CIKM), 2019
Best Refereed Paper Finalist, INFORMS QSR Section.
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Graph Recurrent Networks with Attributed Random Walks
Published in ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2019
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Is a Single Vector Enough? Exploring Node Polysemy for Network Embedding
Published in ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2019
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Deep Structured Cross-Modal Anomaly Detection
Published in IEEE International Joint Conference on Neural Networks (IJCNN), 2019
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