Zhongfang Zhuang

Orcid: 0000-0001-6717-5102

According to our database1, Zhongfang Zhuang authored at least 40 papers between 2014 and 2024.

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Bibliography

2024
Matrix Profile for Anomaly Detection on Multidimensional Time Series.
CoRR, 2024

Preserving Individuality while Following the Crowd: Understanding the Role of User Taste and Crowd Wisdom in Online Product Rating Prediction.
CoRR, 2024

Random Projection Layers for Multidimensional Time Series Forecasting.
CoRR, 2024

Has Your Pretrained Model Improved? A Multi-head Posterior Based Approach.
CoRR, 2024

Analysis of Causal and Non-Causal Convolution Networks for Time Series Classification.
Proceedings of the 2024 SIAM International Conference on Data Mining, 2024

PUPAE: Intuitive and Actionable Explanations for Time Series Anomalies.
Proceedings of the 2024 SIAM International Conference on Data Mining, 2024

RPMixer: Shaking Up Time Series Forecasting with Random Projections for Large Spatial-Temporal Data.
Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2024

A Systematic Evaluation of Generated Time Series and Their Effects in Self-Supervised Pretraining.
Proceedings of the 33rd ACM International Conference on Information and Knowledge Management, 2024

2023
PDT: Pretrained Dual Transformers for Time-aware Bipartite Graphs.
CoRR, 2023

Spatial-Temporal Graph Sandwich Transformer for Traffic Flow Forecasting.
Proceedings of the Machine Learning and Knowledge Discovery in Databases: Applied Data Science and Demo Track, 2023

Multitask Learning for Time Series Data with 2D Convolution.
Proceedings of the International Conference on Machine Learning and Applications, 2023

Interpretable Debiasing of Vectorized Language Representations with Iterative Orthogonalization.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

FATA-Trans: Field And Time-Aware Transformer for Sequential Tabular Data.
Proceedings of the 32nd ACM International Conference on Information and Knowledge Management, 2023

Toward a Foundation Model for Time Series Data.
Proceedings of the 32nd ACM International Conference on Information and Knowledge Management, 2023

An Efficient Content-based Time Series Retrieval System.
Proceedings of the 32nd ACM International Conference on Information and Knowledge Management, 2023

Spatial-Temporal Graph Boosting Networks: Enhancing Spatial-Temporal Graph Neural Networks via Gradient Boosting.
Proceedings of the 32nd ACM International Conference on Information and Knowledge Management, 2023

Sketching Multidimensional Time Series for Fast Discord Mining.
Proceedings of the IEEE International Conference on Big Data, 2023

Ego-Network Transformer for Subsequence Classification in Time Series Data.
Proceedings of the IEEE International Conference on Big Data, 2023

Temporal Treasure Hunt: Content-based Time Series Retrieval System for Discovering Insights.
Proceedings of the IEEE International Conference on Big Data, 2023

Time Series Synthesis Using the Matrix Profile for Anonymization.
Proceedings of the IEEE International Conference on Big Data, 2023

2022
Deep Learning on Attributed Sequences.
CoRR, 2022

Error-bounded Approximate Time Series Joins using Compact Dictionary Representations of Time Series.
Proceedings of the 2022 SIAM International Conference on Data Mining, 2022

Embedding Compression with Hashing for Efficient Representation Learning in Large-Scale Graph.
Proceedings of the KDD '22: The 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Washington, DC, USA, August 14, 2022

PerfSig: Extracting Performance Bug Signatures via Multi-modality Causal Analysis.
Proceedings of the 44th IEEE/ACM 44th International Conference on Software Engineering, 2022

Matrix Profile XXVII: A Novel Distance Measure for Comparing Long Time Series.
Proceedings of the IEEE International Conference on Knowledge Graph, 2022

Learning from Disagreement for Event Detection.
Proceedings of the IEEE International Conference on Big Data, 2022

Quantized Wasserstein Procrustes Alignment of Word Embedding Spaces.
Proceedings of the 15th biennial conference of the Association for Machine Translation in the Americas (Volume 1: Research Track), 2022

2021
Constrained Non-Affine Alignment of Embeddings.
Proceedings of the IEEE International Conference on Data Mining, 2021

Online Multi-horizon Transaction Metric Estimation with Multi-modal Learning in Payment Networks.
Proceedings of the CIKM '21: The 30th ACM International Conference on Information and Knowledge Management, Virtual Event, Queensland, Australia, November 1, 2021

2020
Multi-stream RNN for Merchant Transaction Prediction.
CoRR, 2020

Multi-future Merchant Transaction Prediction.
Proceedings of the Machine Learning and Knowledge Discovery in Databases. Applied Data Science and Demo Track, 2020

Towards a Flexible Embedding Learning Framework.
Proceedings of the 20th International Conference on Data Mining Workshops, 2020

MLAS: Metric Learning on Attributed Sequences.
Proceedings of the 2020 IEEE International Conference on Big Data (IEEE BigData 2020), 2020

Merchant Category Identification Using Credit Card Transactions.
Proceedings of the 2020 IEEE International Conference on Big Data (IEEE BigData 2020), 2020

2019
AMAS: Attention Model for Attributed Sequence Classification.
Proceedings of the 2019 SIAM International Conference on Data Mining, 2019

Attributed Sequence Embedding.
Proceedings of the 2019 IEEE International Conference on Big Data (IEEE BigData), 2019

2018
One-Shot Learning on Attributed Sequences.
Proceedings of the IEEE International Conference on Big Data (IEEE BigData 2018), 2018

2016
PRO: Preference-Aware Recurring Query Optimization.
Proceedings of the 25th ACM International Conference on Information and Knowledge Management, 2016

2015
Shared Execution of Recurring Workloads in MapReduce.
Proc. VLDB Endow., 2015

2014
Redoop Infrastructure for Recurring Big Data Queries.
Proc. VLDB Endow., 2014


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