Zhengzhang Chen

发表

Automated Anomaly Detection via Curiosity-Guided Search and Self-Imitation Learning

D. Zha, Haifeng Chen, Zhengzhang Chen, 2021, IEEE Transactions on Neural Networks and Learning Systems.

Multi-Scale One-Class Recurrent Neural Networks for Discrete Event Sequence Anomaly Detection pdf

Zhiwei Wang, Haifeng Chen, Jiliang Tang, 2020, KDD.

FACESEC: A Fine-grained Robustness Evaluation Framework for Face Recognition Systems

Wei Cheng, Yevgeniy Vorobeychik, Jingchao Ni, 2021, 2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

Dynamic Gaussian Mixture based Deep Generative Model For Robust Forecasting on Sparse Multivariate Time Series pdf

Bo Zong, Yanchi Liu, Yinjun Wu, 2021, AAAI.

Convolutional Transformer based Dual Discriminator Generative Adversarial Networks for Video Anomaly Detection

Xinyang Feng, Jingchao Ni, Dongjin Song, 2021, ACM Multimedia.

Beyond One-Model-Fits-All: A Survey of Domain Specialization for Large Language Models

Quanquan Gu, Carl Yang, Wei Cheng, 2023, ArXiv.

Learning Disentangled Representations for Time Series pdf

Xia Hu, Daochen Zha, Zhengzhang Chen, 2021, ArXiv.

Towards Learning Disentangled Representations for Time Series

Mengnan Du, D. Zha, Haifeng Chen, 2022, KDD.

AutoOD: Neural Architecture Search for Outlier Detection

Haifeng Jin, Xia Hu, Daochen Zha, 2021, 2021 IEEE 37th International Conference on Data Engineering (ICDE).

Disentangled Causal Graph Learning for Online Unsupervised Root Cause Analysis

Yanjie Fu, Yanchi Liu, Haifeng Chen, 2023, ArXiv.

Superclass-Conditional Gaussian Mixture Model For Learning Fine-Grained Embeddings

Wei Cheng, Haifeng Chen, T. Asakura, 2022, ICLR.

Domain Specialization as the Key to Make Large Language Models Disruptive: A Comprehensive Survey

Carl Yang, Wei Cheng, Yanchi Liu, 2023, 2305.18703.

Interpretable Time-series Representation Learning With Multi-Level Disentanglement

Xia Hu, Mengnan Du, D. Zha, 2021 .

AutoOD: Automated Outlier Detection via Curiosity-guided Search and Self-imitation Learning pdf

Haifeng Chen, Haifeng Jin, Xia Hu, 2020, ArXiv.

Beyond One-Model-Fits-All: A Survey of Domain Specialization for Large Language Models

Quanquan Gu, Carl Yang, Wei Cheng, 2023, ArXiv.

Interpreting Convolutional Sequence Model by Learning Local Prototypes with Adaptation Regularization

Bo Zong, Yanchi Liu, Jingchao Ni, 2021, CIKM.

Towards Robust Graph Neural Networks via Adversarial Contrastive Learning

Haifeng Chen, Zhengzhang Chen, Jingchao Ni, 2022, 2022 IEEE International Conference on Big Data (Big Data).

Incremental Causal Graph Learning for Online Root Cause Analysis

Yanjie Fu, Yanchi Liu, Zhengzhang Chen, 2023, KDD.

Hierarchical Graph Neural Networks for Causal Discovery and Root Cause Localization

Zheng Wang, Yanjie Fu, Liang Tong, 2023, ArXiv.

APTrace: A Responsive System for Agile Enterprise Level Causality Analysis

Mu Zhang, Xusheng Xiao, Kangkook Jee, 2020, 2020 IEEE 36th International Conference on Data Engineering (ICDE).

Domain Specialization as the Key to Make Large Language Models Disruptive: A Comprehensive Survey

Carl Yang, Wei Cheng, Yanchi Liu, 2023, 2305.18703.

Unsupervised Document Embedding via Contrastive Augmentation pdf

Wei Cheng, Bo Zong, Yanchi Liu, 2021, ArXiv.

POND: Multi-Source Time Series Domain Adaptation with Information-Aware Prompt Tuning

Junxiang Wang, Haifeng Chen, Liang Zhao, 2023, 2312.12276.

Prompt-based Domain Discrimination for Multi-source Time Series Domain Adaptation

Junxiang Wang, Liang Zhao, Zhengzhang Chen, 2023, arXiv.org.

MULAN: Multi-modal Causal Structure Learning and Root Cause Analysis for Microservice Systems

Lecheng Zheng, Haifeng Chen, Zhengzhang Chen, 2024, WWW.

Multi-modal Causal Structure Learning and Root Cause Analysis

Lecheng Zheng, Zhengzhang Chen, Haifeng Chen, 2024, ArXiv.