Papers

Preprints

• [Dec. 23] Multi-Task Models Adversarial Attacks. [PDF]
  Lijun Zhang, Xiao Liu, Kaleel Mahmood, Caiwen Ding, Hui Guan.

Publicactions

• [NeurIPS’24] Attack-Resilient Image Watermarking Using Stable Diffusion. [PDF][Code]
  Lijun Zhang, Xiao Liu, Antoni Viros Martin, Cindy Xiong Bearfield, Yuriy Brun, Hui Guan.

• [NeurIPS’24] Thinking Forward: Memory-Efficient Federated Finetuning of Language Models. [PDF]
  Kunjal Panchal, Nisarg Parikh, Sunav Choudhary, Lijun Zhang, Yuriy Brun, Hui Guan.

• [EuroSys’24] GMorph: Accelerating Multi-DNN Inference via Model Fusion. [PDF][Code]
  Qizheng Yang, Tianyi Yang, Mingcan Xiang, Lijun Zhang, Haoliang Wang, Marco Serafini, Hui Guan.
  The 2024 European Conference on Computer Systems (EuroSys), April 22-25, 2024.

• [NeurIPS’23] Flow: Per-instance Personalized Federated Learning. [PDF][Code]
  Kunjal Panchal, Sunav Choudhary, Nisarg Parikh, Lijun Zhang, Hui Guan.
  The 2023 Conference on Neural Information Processing Systems, Dec. 10-16, 2023.

• [TNNLS’23] A Tree-Structured Multi-Task Model Architectures Recommendation System. [PDF][Code]
  Lijun Zhang, Xiao Liu, Hui Guan.
  IEEE Transactions on Neural Networks and Learning Systems, 2023.

• [IEEE Access’23] An Alternative Hard-Parameter Sharing Paradigm for Multi-Domain Learning. [PDF]
  Lijun Zhang, Qizheng Yang, Xiao Liu, Hui Guan.
  In IEEE Access, 2023.

• [NeurIPS’22] AutoMTL: A Programming Framework for Automating Efficient Multi-Task Learning. [PDF][Code]
  Lijun Zhang, Xiao Liu, Hui Guan.
  36th Conference on Neural Information Processing Systems (NeurIPS 2022), November 28, 2022. (Acceptance rate: 25.6%)

• [AutoML’22] A Tree-Structured Multi-Task Model Recommender. [PDF][Code][Teaser][Video]
  Lijun Zhang, Xiao Liu, Hui Guan.
  1st International Conference on Automated Machine Learning, July 25-27, 2022. (Acceptance rate: 19.2%)

• [ICME’22] Rethinking Hard-Parameter Sharing in Multi-Domain Learning. [PDF]
  Lijun Zhang, Qizheng Yang, Xiao Liu, Hui Guan.
  IEEE INTERNATIONAL CONFERENCE ON MULTIMEDIA AND EXPO (ICME), Taipei, Taiwan, July 18-22, 2022. (Acceptance rate: 29%)

• [ICDM’21] Recurrent Neural Networks Meet Context-Free Grammar: Two Birds with One Stone. [PDF]
  Hui Guan, Umang Chaudhary, Yuanchao Xu, Lin Ning, Lijun Zhang, and Xipeng Shen.
  In IEEE International Conference on Data Mining, 2021 (short paper). (Acceptance rate: 20% (198/990))

• [InformationSystems’21] Reuse-Centric K-Means Configuration. [PDF]]
  Lijun Zhang, Hui Guan, Yufei Ding, Xipeng Shen, Hamid Krim.
  Information Systems, 2021.

• [ACMMM’19] Zero-Shot Restoration of Back-lit Images Using Deep Internal Learning. [PDF][Code]
  Lin Zhang, Lijun Zhang, Xiao Liu, Ying Shen, Shaoming Zhang, Shengjie Zhao.
  ACM International Conference on Multimedia, 2019. (Acceptance rate: 26.5%)

• [ICME’18] Image Exposure Assessment: A Benchmark and A Deep Convolutional Neural Networks Based Model. [PDF]
  Lijun Zhang, Lin Zhang, Xiao Liu, Ying Shen, Dongqing Wang.
  IEEE INTERNATIONAL CONFERENCE ON MULTIMEDIA AND EXPO (ICME), 2018.

• [ICONIP’17] Illumination Quality Assessment for Face Images: A Benchmark and a Convolutional Neural Networks Based Model. [PDF][Code]
  Lijun Zhang, Lin Zhang, Lida Li.
  International Conference on Neural Information Processing, 2017.