Zhang, Nevin L.

19 publications

ICML 2025 COSDA: Counterfactual-Based Susceptibility Risk Framework for Open-Set Domain Adaptation Wenxu Wang, Rui Zhou, Jing Wang, Yun Zhou, Cheng Zhu, Ruichun Tang, Bo Han, Nevin L. Zhang

AAAI 2025 Test-Time Adaptation on Noisy Data via Model-Pruning-Based Filtering and Flatness-Aware Entropy Minimization Xingzhi Zhou, Zhiliang Tian, Boyang Zhang, Yibo Zhang, Ka Chun Cheung, Simon See, Hao Yang, Yun Zhou, Nevin L. Zhang

ICMLW 2024 Dual Risk Minimization for Robust Fine-Tuning of Zero-Shot Models Kaican Li, Weiyan Xie, Ricardo Silva, Nevin L. Zhang

NeurIPS 2024 Dual Risk Minimization: Towards Next-Level Robustness in Fine-Tuning Zero-Shot Models Kaican Li, Weiyan Xie, Yongxiang Huang, Didan Deng, Lanqing Hong, Zhenguo Li, Ricardo Silva, Nevin L. Zhang

NeurIPS 2024 Uncovering, Explaining, and Mitigating the Superficial Safety of Backdoor Defense Rui Min, Zeyu Qin, Nevin L. Zhang, Li Shen, Minhao Cheng

NeurIPSW 2023 Robustness May Be More Brittle than We Think Under Different Degrees of Distribution Shifts Kaican Li, Yifan Zhang, Lanqing Hong, Zhenguo Li, Nevin L. Zhang

UAI 2023 Two-Stage Holistic and Contrastive Explanation of Image Classification Weiyan Xie, Xiao-Hui Li, Zhi Lin, Leonard K. M. Poon, Caleb Chen Cao, Nevin L. Zhang

IJCAI 2023 ViT-CX: Causal Explanation of Vision Transformers Weiyan Xie, Xiao-Hui Li, Caleb Chen Cao, Nevin L. Zhang

NeurIPS 2022 SeqPATE: Differentially Private Text Generation via Knowledge Distillation Zhiliang Tian, Yingxiu Zhao, Ziyue Huang, Yu-Xiang Wang, Nevin L. Zhang, He He

AAAI 2021 Learning from My Friends: Few-Shot Personalized Conversation Systems via Social Networks Zhiliang Tian, Wei Bi, Zihan Zhang, Dongkyu Lee, Yiping Song, Nevin L. Zhang

AAAI 2020 Not All Attention Is Needed: Gated Attention Network for Sequence Data Lanqing Xue, Xiaopeng Li, Nevin L. Zhang

ICLR 2019 Learning Latent Superstructures in Variational Autoencoders for Deep Multidimensional Clustering Xiaopeng Li, Zhourong Chen, Leonard K. M. Poon, Nevin L. Zhang

IJCAI 2018 Building Sparse Deep Feedforward Networks Using Tree Receptive Fields Xiaopeng Li, Zhourong Chen, Nevin L. Zhang

AAAI 2017 Latent Tree Analysis Nevin L. Zhang, Leonard K. M. Poon

AAAI 2017 Sparse Boltzmann Machines with Structure Learning as Applied to Text Analysis Zhourong Chen, Nevin L. Zhang, Dit-Yan Yeung, Peixian Chen

AAAI 2016 Progressive EM for Latent Tree Models and Hierarchical Topic Detection Peixian Chen, Nevin L. Zhang, Leonard K. M. Poon, Zhourong Chen

CVPR 2015 Bayesian Adaptive Matrix Factorization with Automatic Model Selection Peixian Chen, Naiyan Wang, Nevin L. Zhang, Dit-Yan Yeung

UAI 2014 Proceedings of the Thirtieth Conference on Uncertainty in Artificial Intelligence, UAI 2014, Quebec City, Quebec, Canada, July 23-27, 2014 Nevin L. Zhang, Jin Tian

JMLR 2004 Hierarchical Latent Class Models for Cluster Analysis Nevin L. Zhang