A novel model: Dynamic choice artificial neural network (DCANN) for an electricity price forecasting system. - Jianzhou Wang; Feng Liu 003; Yiliao Song; Jing Zhao (Appl. Soft Comput., 2016)

Heterogeneous unsupervised domain adaptation based on fuzzy feature fusion. - Feng Liu 003; Guangquan Zhang 001; Jie Lu 001 (FUZZ-IEEE, 2017)

Heterogeneous Unsupervised Cross-domain Transfer Learning. - Feng Liu 003; Guangquan Zhang 001; Haiyan Lu; Jie Lu 001 (CoRR, 2017)

A cross-domain recommender system with consistent information transfer. - Qian Zhang 023; Dianshuang Wu; Jie Lu 001; Feng Liu 003; Guangquan Zhang 001 (Decis. Support Syst., 2017)

Unconstrained fuzzy feature fusion for heterogeneous unsupervised domain adaptation. - Feng Liu 003; Guangquan Zhang 001; Jie Lu 001 (FUZZ-IEEE, 2018)

Does deep learning help topic extraction? A kernel k-means clustering method with word embedding. - Yi Zhang 095; Jie Lu 001; Feng Liu 003; Qian Liu 012; Alan L. Porter; Hongshu Chen; Guangquan Zhang 001 (J. Informetrics, 2018)

Accumulating regional density dissimilarity for concept drift detection in data streams. - Anjin Liu; Jie Lu 001; Feng Liu 003; Guangquan Zhang 001 (Pattern Recognit., 2018)

Unsupervised Heterogeneous Domain Adaptation via Shared Fuzzy Equivalence Relations. - Feng Liu 003; Jie Lu 001; Guangquan Zhang 001 (IEEE Trans. Fuzzy Syst., 2018)

A Novel Fuzzy Neural Network for Unsupervised Domain Adaptation in Heterogeneous Scenarios. - Feng Liu 003; Guangquan Zhang 001; Jie Lu 001 (FUZZ-IEEE, 2019)

Unsupervised Domain Adaptation with Sphere Retracting Transformation. - Zhen Fang 001; Jie Lu 001; Feng Liu 003; Guangquan Zhang 001 (IJCNN, 2019)

Butterfly: A Panacea for All Difficulties in Wildly Unsupervised Domain Adaptation. - Feng Liu 003; Jie Lu 001; Bo Han 003; Gang Niu 001; Guangquan Zhang 001; Masashi Sugiyama (CoRR, 2019)

Fuzzy Transfer Learning Using an Infinite Gaussian Mixture Model and Active Learning. - Hua Zuo; Jie Lu 001; Guangquan Zhang 001; Feng Liu 003 (IEEE Trans. Fuzzy Syst., 2019)

A Novel Non-parametric Two-Sample Test on Imprecise Observations. - Feng Liu 003; Guangquan Zhang 001; Jie Lu 001 (FUZZ-IEEE, 2020)

Learning Deep Kernels for Non-Parametric Two-Sample Tests. - Feng Liu 003; Wenkai Xu; Jie Lu 001; Guangquan Zhang 001; Arthur Gretton; Danica J. Sutherland (ICML, 2020)

Clarinet: A One-step Approach Towards Budget-friendly Unsupervised Domain Adaptation. - Yiyang Zhang; Feng Liu 003; Zhen Fang 001; Bo Yuan 003; Guangquan Zhang 001; Jie Lu 001 (IJCAI, 2020)

Maximum Mean Discrepancy is Aware of Adversarial Attacks. - Ruize Gao; Feng Liu 003; Jingfeng Zhang; Bo Han 003; Tongliang Liu; Gang Niu 001; Masashi Sugiyama (CoRR, 2020)

Heterogeneous Domain Adaptation: An Unsupervised Approach. - Feng Liu 003; Guangquan Zhang 001; Jie Lu 001 (IEEE Trans. Neural Networks Learn. Syst., 2020)

Towards Realistic Transfer Learning Methods: Theory and Algorithms - Feng Liu 003 (2020)

How Does the Combined Risk Affect the Performance of Unsupervised Domain Adaptation Approaches? - Zhong Li 001; Zhen Fang 001; Feng Liu 003; Jie Lu 001; Bo Yuan 003; Guangquan Zhang 001 (AAAI, 2021)

Learning from Imprecise Observations: An Estimation Error Bound based on Fuzzy Random Variables. - Guangzhi Ma; Feng Liu 003; Guangquan Zhang 001; Jie Lu 001 (FUZZ-IEEE, 2021)

Learning Bounds for Open-Set Learning. - Zhen Fang 001; Jie Lu 001; Anjin Liu; Feng Liu 003; Guangquan Zhang 001 (ICML, 2021)

Maximum Mean Discrepancy Test is Aware of Adversarial Attacks. - Ruize Gao; Feng Liu 003; Jingfeng Zhang; Bo Han 003; Tongliang Liu; Gang Niu 001; Masashi Sugiyama (ICML, 2021)

TOHAN: A One-step Approach towards Few-shot Hypothesis Adaptation. - Haoang Chi; Feng Liu 003; Wenjing Yang 002; Long Lan; Tongliang Liu; Bo Han 003; William K. Cheung 001; James T. Kwok (NeurIPS, 2021)

Meta Two-Sample Testing: Learning Kernels for Testing with Limited Data. - Feng Liu 003; Wenkai Xu; Jie Lu 001; Danica J. Sutherland (NeurIPS, 2021)

Probabilistic Margins for Instance Reweighting in Adversarial Training. - Qizhou Wang; Feng Liu 003; Bo Han 003; Tongliang Liu; Chen Gong 002; Gang Niu 001; Mingyuan Zhou; Masashi Sugiyama (NeurIPS, 2021)

Meta Discovery: Learning to Discover Novel Classes given Very Limited Data. - Haoang Chi; Feng Liu 003; Wenjing Yang 002; Long Lan; Tongliang Liu; Gang Niu 001; Bo Han 003 (CoRR, 2021)

KRADA: Known-region-aware Domain Alignment for Open World Semantic Segmentation. - Chenhong Zhou; Feng Liu 003; Chen Gong 002; Tongliang Liu; Bo Han 003; William Kwok-Wai Cheung (CoRR, 2021)

Local Reweighting for Adversarial Training. - Ruize Gao; Feng Liu 003; Kaiwen Zhou; Gang Niu 001; Bo Han 003; James Cheng (CoRR, 2021)

Multisource Heterogeneous Unsupervised Domain Adaptation via Fuzzy Relation Neural Networks. - Feng Liu 003; Guangquan Zhang 001; Jie Lu 001 (IEEE Trans. Fuzzy Syst., 2021)

Open Set Domain Adaptation: Theoretical Bound and Algorithm. - Zhen Fang 001; Jie Lu 001; Feng Liu 003; Junyu Xuan; Guangquan Zhang 001 (IEEE Trans. Neural Networks Learn. Syst., 2021)

Meta Discovery: Learning to Discover Novel Classes given Very Limited Data. - Haoang Chi; Feng Liu 003; Wenjing Yang 002; Long Lan; Tongliang Liu; Bo Han 003; Gang Niu 001; Mingyuan Zhou; Masashi Sugiyama (ICLR, 2022)

Fast and Reliable Evaluation of Adversarial Robustness with Minimum-Margin Attack. - Ruize Gao; Jiongxiao Wang; Kaiwen Zhou; Feng Liu 003; Binghui Xie; Gang Niu 001; Bo Han 003; James Cheng (ICML, 2022)

Adversarial Attack and Defense for Non-Parametric Two-Sample Tests. - Xilie Xu; Jingfeng Zhang; Feng Liu 003; Masashi Sugiyama; Mohan S. Kankanhalli (ICML, 2022)

Bilateral Dependency Optimization: Defending Against Model-inversion Attacks. - Xiong Peng; Feng Liu 003; Jingfeng Zhang; Long Lan; Junjie Ye; Tongliang Liu; Bo Han 003 (KDD, 2022)

Is Out-of-Distribution Detection Learnable? - Zhen Fang 001; Yixuan Li 001; Jie Lu 001; Jiahua Dong 001; Bo Han 003; Feng Liu 003 (NeurIPS, 2022)

Watermarking for Out-of-distribution Detection. - Qizhou Wang; Feng Liu 003; Yonggang Zhang 003; Jing Zhang 037; Chen Gong 002; Tongliang Liu; Bo Han 003 (NeurIPS, 2022)

Adversarial Attacks and Defense for Non-Parametric Two-Sample Tests. - Xilie Xu; Jingfeng Zhang; Feng Liu 003; Masashi Sugiyama; Mohan S. Kankanhalli (CoRR, 2022)

Multi-class Classification with Fuzzy-feature Observations: Theory and Algorithms. - Guangzhi Ma; Jie Lu 001; Feng Liu 003; Zhen Fang 001; Guangquan Zhang 001 (CoRR, 2022)

Bilateral Dependency Optimization: Defending Against Model-inversion Attacks. - Xiong Peng; Feng Liu 003; Jingfen Zhang; Long Lan; Junjie Ye; Tongliang Liu; Bo Han 003 (CoRR, 2022)

A Drift Region-Based Data Sample Filtering Method. - Fan Dong; Jie Lu 001; Yiliao Song; Feng Liu 003; Guangquan Zhang 001 (IEEE Trans. Cybern., 2022)

Learning From a Complementary-Label Source Domain: Theory and Algorithms. - Yiyang Zhang; Feng Liu 003; Zhen Fang 001; Bo Yuan 003; Guangquan Zhang 001; Jie Lu 001 (IEEE Trans. Neural Networks Learn. Syst., 2022)

Take a Close Look at the Optimization of Deep Kernels for Non-parametric Two-Sample Tests. - Xunye Tian; Feng Liu 003 (ADC, 2023)

Designing Fair AI Systems: How Explanation specificity Influences Users’ Perceived Fairness and Trusting Intentions. - Yiliao Song; Tingru Cui; Feng Liu 003 (ECIS, 2023)

Partition Speeds Up Learning Implicit Neural Representations Based on Exponential-Increase Hypothesis. - Ke Liu 013; Feng Liu 003; Haishuai Wang; Ning Ma; Jiajun Bu; Bo Han 003 (ICCV, 2023)

Out-of-distribution Detection with Implicit Outlier Transformation. - Qizhou Wang; Junjie Ye; Feng Liu 003; Quanyu Dai; Marcus Kalander; Tongliang Liu; Jianye Hao; Bo Han 003 (ICLR, 2023)

Diversity-enhancing Generative Network for Few-shot Hypothesis Adaptation. - Ruijiang Dong; Feng Liu 003; Haoang Chi; Tongliang Liu; Mingming Gong; Gang Niu 001; Masashi Sugiyama; Bo Han 003 (ICML, 2023)

Detecting Out-of-distribution Data through In-distribution Class Prior. - Xue Jiang; Feng Liu 003; Zhen Fang 001; Hong Chen 004; Tongliang Liu; Feng Zheng; Bo Han 003 (ICML, 2023)

Detecting Adversarial Data by Probing Multiple Perturbations Using Expected Perturbation Score. - Shuhai Zhang; Feng Liu 003; Jiahao Yang; Yifan Yang; Changsheng Li; Bo Han 003; Mingkui Tan (ICML, 2023)

Learning to Augment Distributions for Out-of-distribution Detection. - Qizhou Wang; Zhen Fang 001; Yonggang Zhang 003; Feng Liu 003; Yixuan Li 001; Bo Han 003 (NeurIPS, 2023)

Enhancing Adversarial Contrastive Learning via Adversarial Invariant Regularization. - Xilie Xu; Jingfeng Zhang; Feng Liu 003; Masashi Sugiyama; Mohan S. Kankanhalli (NeurIPS, 2023)

Efficient Adversarial Contrastive Learning via Robustness-Aware Coreset Selection. - Xilie Xu; Jingfeng Zhang; Feng Liu 003; Masashi Sugiyama; Mohan S. Kankanhalli (NeurIPS, 2023)

Out-of-distribution Detection Learning with Unreliable Out-of-distribution Sources. - Haotian Zheng; Qizhou Wang; Zhen Fang 001; Xiaobo Xia; Feng Liu 003; Tongliang Liu; Bo Han 003 (NeurIPS, 2023)

Designing Fair AI Systems: Exploring the Interaction of Explainable AI and Task Objectivity on Users' Fairness Perception. - Tingru Cui; Sharon Li 001; Kaiping Chen; James Bailey 001; Feng Liu 003 (PACIS, 2023)

Semi-Supervised Heterogeneous Domain Adaptation: Theory and Algorithms. - Zhen Fang 001; Jie Lu 001; Feng Liu 003; Guangquan Zhang 001 (IEEE Trans. Pattern Anal. Mach. Intell., 2023)

KRADA: Known-region-aware Domain Alignment for Open-set Domain Adaptation in Semantic Segmentation. - Chenhong Zhou; Feng Liu 003; Chen Gong 002; Rongfei Zeng; Tongliang Liu; Kwok-Wai Cheung 001; Bo Han 003 (Trans. Mach. Learn. Res., 2023)

Bridging the Theoretical Bound and Deep Algorithms for Open Set Domain Adaptation. - Zhong Li 001; Zhen Fang 001; Feng Liu 003; Bo Yuan 003; Guangquan Zhang 001; Jie Lu 001 (IEEE Trans. Neural Networks Learn. Syst., 2023)

Negative Label Guided OOD Detection with Pretrained Vision-Language Models. - Xue Jiang; Feng Liu 003; Zhen Fang 001; Hong Chen 004; Tongliang Liu; Feng Zheng; Bo Han 003 (ICLR, 2024)

Visual-Text Cross Alignment: Refining the Similarity Score in Vision-Language Models. - Jinhao Li 004; Haopeng Li; Sarah Monazam Erfani; Lei Feng 006; James Bailey 001; Feng Liu 003 (ICML, 2024)

Sample-specific Masks for Visual Reprogramming-based Prompting. - Chengyi Cai; Zesheng Ye; Lei Feng 006; Jianzhong Qi 001; Feng Liu 003 (ICML, 2024)

MOKD: Cross-domain Finetuning for Few-shot Classification via Maximizing Optimized Kernel Dependence. - Hongduan Tian; Feng Liu 003; Tongliang Liu; Bo Du 001; Yiu-ming Cheung; Bo Han 003 (ICML, 2024)

Optimal Kernel Choice for Score Function-based Causal Discovery. - Wenjie Wang; Biwei Huang; Feng Liu 003; Xinge You; Tongliang Liu; Kun Zhang 001; Mingming Gong (ICML, 2024)

Improving Accuracy-robustness Trade-off via Pixel Reweighted Adversarial Training. - Jiacheng Zhang; Feng Liu 003; Dawei Zhou 004; Jingfeng Zhang; Tongliang Liu (ICML, 2024)

Candidate Pseudolabel Learning: Enhancing Vision-Language Models by Prompt Tuning with Unlabeled Data. - Jiahan Zhang; Qi Wei 004; Feng Liu 003; Lei Feng 006 (ICML, 2024)

Bayesian-guided Label Mapping for Visual Reprogramming. - Chengyi Cai; Zesheng Ye; Lei Feng 006; Jianzhong Qi 001; Feng Liu 003 (NeurIPS, 2024)

Unveiling Causal Reasoning in Large Language Models: Reality or Mirage? - Haoang Chi; He Li; Wenjing Yang 002; Feng Liu 003; Long Lan; Xiaoguang Ren; Tongliang Liu; Bo Han 003 (NeurIPS, 2024)

In-N-Out: Lifting 2D Diffusion Prior for 3D Object Removal via Tuning-Free Latents Alignment. - Dongting Hu; Huan Fu; Jiaxian Guo; Liuhua Peng; Tingjin Chu; Feng Liu 003; Tongliang Liu; Mingming Gong (NeurIPS, 2024)

Pseudo-Private Data Guided Model Inversion Attacks. - Xiong Peng; Bo Han 003; Feng Liu 003; Tongliang Liu; Mingyuan Zhou (NeurIPS, 2024)

Mind the Gap Between Prototypes and Images in Cross-domain Finetuning. - Hongduan Tian; Feng Liu 003; Zhanke Zhou; Tongliang Liu; Chengqi Zhang; Bo Han 003 (NeurIPS, 2024)

BDetCLIP: Multimodal Prompting Contrastive Test-Time Backdoor Detection. - Yuwei Niu; Shuo He 001; Qi Wei 004; Feng Liu 003; Lei Feng 006 (CoRR, 2024)

Exclusive Style Removal for Cross Domain Novel Class Discovery. - Yicheng Wang; Feng Liu 003; Junmin Liu; Zhen Fang 001; Kai Sun 007 (CoRR, 2024)

Fast Information Streaming Handler (FisH): A Unified Seismic Neural Network for Single Station Real-Time Earthquake Early Warning. - Tianning Zhang; Feng Liu 003; Yuming Yuan; Rui Su; Wanli Ouyang; Lei Bai 001 (CoRR, 2024)

Learning Deep Kernels for Non-Parametric Independence Testing. - Nathaniel Xu; Feng Liu 003; Danica J. Sutherland (CoRR, 2024)

TED-VITON: Transformer-Empowered Diffusion Models for Virtual Try-On. - Zhenchen Wan; Yanwu Xu 003; Zhaoqing Wang; Feng Liu 003; Tongliang Liu; Mingming Gong (CoRR, 2024)

DualCast: Disentangling Aperiodic Events from Traffic Series with a Dual-Branch Model. - Xinyu Su; Feng Liu 003; Yanchuan Chang; Egemen Tanin; Majid Sarvi; Jianzhong Qi 001 (CoRR, 2024)

Adversarial Purification by Consistency-aware Latent Space Optimization on Data Manifolds. - Shuhai Zhang; Jiahao Yang; Hui Luo 002; Jie Chen; Li Wang 033; Feng Liu 003; Bo Han 003; Mingkui Tan (CoRR, 2024)

On the Learnability of Out-of-distribution Detection. - Zhen Fang 001; Yixuan Li 001; Feng Liu 003; Bo Han 003; Jie Lu 001 (J. Mach. Learn. Res., 2024)

HiFE: Hierarchical Feature Ensemble Framework for Few-shot Hypotheses Adaptation. - Yongfeng Zhong; Haoang Chi; Feng Liu 003; Xiao-Ming Wu; Bo Han 003 (Trans. Mach. Learn. Res., 2024)

Multiclass Classification With Fuzzy-Feature Observations: Theory and Algorithms. - Guangzhi Ma; Jie Lu 001; Feng Liu 003; Zhen Fang 001; Guangquan Zhang 001 (IEEE Trans. Cybern., 2024)

Domain Adaptation With Interval-Valued Observations: Theory and Algorithms. - Guangzhi Ma; Jie Lu 001; Feng Liu 003; Zhen Fang 001; Guangquan Zhang 001 (IEEE Trans. Fuzzy Syst., 2024)

Does Confusion Really Hurt Novel Class Discovery? - Haoang Chi; Wenjing Yang 002; Feng Liu 003; Long Lan; Tao Qin; Bo Han 003 (Int. J. Comput. Vis., 2024)

Attribute-based Visual Reprogramming for Vision-Language Models. - Chengyi Cai; Zesheng Ye; Lei Feng 006; Jianzhong Qi 001; Feng Liu 003 (ICLR, 2025)

Deep Kernel Relative Test for Machine-generated Text Detection. - Yiliao Song; Zhenqiao Yuan; Shuhai Zhang; Zhen Fang 001; Jun Yu; Feng Liu 003 (ICLR, 2025)

Endowing Visual Reprogramming with Adversarial Robustness. - Shengjie Zhou; Xin Cheng 007; Haiyang Xu 001; Ming Yan 008; Tao Xiang 001; Feng Liu 003; Lei Feng 006 (ICLR, 2025)

A Unified Data Representation Learning for Non-parametric Two-sample Testing. - Xunye Tian; Liuhua Peng; Zhijian Zhou; Mingming Gong; Arthur Gretton; Feng Liu 003 (UAI, 2025)

50 Shades of Deceptive Patterns: A Unified Taxonomy, Multimodal Detection, and Security Implications. - Zewei Shi; Ruoxi Sun 001; Jieshan Chen; Jiamou Sun; Minhui Xue 001; Yansong Gao 001; Feng Liu 003; Xingliang Yuan (WWW, 2025)

Trustworthy AI under Imperfect Web Data. - Jiangchao Yao; Feng Liu 003; Bo Han 003 (WWW (Companion Volume), 2025)

Exclusive style removal for cross domain novel class discovery. - Yicheng Wang; Feng Liu 003; Junmin Liu; Kai Sun 007 (Neural Networks, 2025)

Exploring Weak-to-Strong Generalization for CLIP-based Classification. - Jinhao Li 004; Sarah Monazam Erfani; Lei Feng 006; James Bailey 001; Feng Liu 003 (Trans. Mach. Learn. Res., 2025)

DispFormer: Pretrained Transformer for Flexible Dispersion Curve Inversion from Global Synthesis to Regional Applications. - Feng Liu 003; Bao Deng; Rui Su; Lei Bai 001; Wanli Ouyang (CoRR, 2025)

Attribute-based Visual Reprogramming for Image Classification with CLIP. - Chengyi Cai; Zesheng Ye; Lei Feng 006; Jianzhong Qi 001; Feng Liu 003 (CoRR, 2025)

Membership Inference Attack Should Move On to Distributional Statistics for Distilled Generative Models. - Muxing Li; Zesheng Ye; Yixuan Li 001; Andy Song; Guangquan Zhang 001; Feng Liu 003 (CoRR, 2025)

Transforming Weather Data from Pixel to Latent Space. - Sijie Zhao; Feng Liu 003; Xueliang Zhang 002; Hao Chen 045; Tao Han 002; Junchao Gong; Ran Tao; Pengfeng Xiao; Lei Bai 001; Wanli Ouyang (CoRR, 2025)

MF-VITON: High-Fidelity Mask-Free Virtual Try-On with Minimal Input. - Zhenchen Wan; Yanwu Xu 003; Dongting Hu; Weilun Cheng; Tianxi Chen; Zhaoqing Wang; Feng Liu 003; Tongliang Liu; Mingming Gong (CoRR, 2025)

GRU: Mitigating the Trade-off between Unlearning and Retention for Large Language Models. - Yue Wang; Qizhou Wang; Feng Liu 003; Wei Huang; Yali Du 001; Xiaojiang Du; Bo Han 003 (CoRR, 2025)

Temporal-Spectral-Spatial Unified Remote Sensing Dense Prediction. - Sijie Zhao; Feng Liu 003; Xueliang Zhang 002; Hao Chen 045; Pengfeng Xiao; Lei Bai 001 (CoRR, 2025)

OmniEarth-Bench: Towards Holistic Evaluation of Earth's Six Spheres and Cross-Spheres Interactions with Multimodal Observational Earth Data. - Fengxiang Wang 004; Mingshuo Chen; Xuming He; Yifan Zhang; Feng Liu 003; Zijie Guo; Zhenghao Hu; Jiong Wang; Jingyi Xu; Zhangrui Li; Fenghua Ling; Ben Fei; et al. (CoRR, 2025)

Multiview Classification Through Learning From Interval-Valued Data. - Guangzhi Ma; Jie Lu 001; Zhen Fang 001; Feng Liu 003; Guangquan Zhang 001 (IEEE Trans. Neural Networks Learn. Syst., 2025)

Understanding Model Reprogramming for CLIP via Decoupling Visual Prompts. - Chengyi Cai; Zesheng Ye; Lei Feng 006; Jianzhong Qi 001; Feng Liu 003 (CoRR, 2025)

Neural Network Reprogrammability: A Unified Theme on Model Reprogramming, Prompt Tuning, and Prompt Instruction. - Zesheng Ye; Chengyi Cai; Ruijiang Dong; Jianzhong Qi 001; Lei Feng 006; Pin-Yu Chen; Feng Liu 003 (CoRR, 2025)

Generalising Traffic Forecasting to Regions without Traffic Observations. - Xinyu Su; Majid Sarvi; Feng Liu 003; Egemen Tanin; Jianzhong Qi 001 (CoRR, 2025)

Unknown-Aware Bilateral Dependency Optimization for Defending Against Model Inversion Attacks. - Xiong Peng; Feng Liu 003; Nannan Wang 001; Long Lan; Tongliang Liu; Yiu-Ming Cheung; Bo Han 003 (IEEE Trans. Pattern Anal. Mach. Intell., 2025)