Predicting Seizures from Electroencephalography Recordings: A Knowledge Transfer Strategy. - Jian Liang 002; Rui Lu; Changshui Zhang; Fei Wang 001 (ICHI, 2016)

Poster Paper: Predicting Seizures from Electroencephalography Recordings: A Knowledge Transfer Strategy. - Jian Liang 002; Rui Lu; Changshui Zhang; Fei Wang 001 (ICHI, 2016)

DeepFish: Accurate underwater live fish recognition with a deep architecture. - Hongwei Qin; Xiu Li 001; Jian Liang 002; YiGang Peng; Changshui Zhang (Neurocomputing, 2016)

An RNN Architecture with Dynamic Temporal Matching for Personalized Predictions of Parkinson's Disease. - Chao Che; Cao Xiao; Jian Liang 002; Bo Jin 001; Jiayu Zho; Fei Wang 001 (SDM, 2017)

Weakly- and Semi-Supervised Object Detection with Expectation-Maximization Algorithm. - Ziang Yan; Jian Liang 002; Weishen Pan; Jin Li 020; Changshui Zhang (CoRR, 2017)

Robust finite mixture regression for heterogeneous targets. - Jian Liang 002; Kun Chen 002; Ming Lin 002; Changshui Zhang; Fei Wang 001 (Data Min. Knowl. Discov., 2018)

Leveraging mixed and incomplete outcomes via reduced-rank modeling. - Chongliang Luo; Jian Liang 002; Gen Li 004; Fei Wang 001; Changshui Zhang; Dipak K. Dey; Kun Chen 002 (J. Multivar. Anal., 2018)

Selection Bias Explorations and Debias Methods for Natural Language Sentence Matching Datasets. - Guanhua Zhang; Bing Bai; Jian Liang 002; Kun Bai; Shiyu Chang; Mo Yu; Conghui Zhu; Tiejun Zhao (ACL (1), 2019)

Additive Adversarial Learning for Unbiased Authentication. - Jian Liang 002; Yuren Cao; Chenbin Zhang; Shiyu Chang; Kun Bai; Zenglin Xu (CVPR, 2019)

Two Sides of the Same Coin: White-box and Black-box Attacks for Transfer Learning. - Yinghua Zhang; Yangqiu Song; Jian Liang 002; Kun Bai; Qiang Yang 001 (KDD, 2020)

Hybrid Differentially Private Federated Learning on Vertically Partitioned Data. - Chang Wang; Jian Liang 002; Mingkai Huang; Bing Bai; Kun Bai; Hao Li (CoRR, 2020)

Domain Agnostic Learning for Unbiased Authentication. - Jian Liang 002; Yuren Cao; Shuang Li 008; Bing Bai; Hao Li; Fei Wang 001; Kun Bai (CoRR, 2020)

Reliable Evaluations for Natural Language Inference based on a Unified Cross-dataset Benchmark. - Guanhua Zhang; Bing Bai; Jian Liang 002; Kun Bai; Conghui Zhu; Tiejun Zhao (CoRR, 2020)

Relation-Guided Representation Learning. - Zhao Kang 001; Xiao Lu 004; Jian Liang 002; Kun Bai; Zenglin Xu (Neural Networks, 2020)

Bi-Classifier Determinacy Maximization for Unsupervised Domain Adaptation. - Shuang Li 008; Fangrui Lv; Binhui Xie; Chi Harold Liu; Jian Liang 002; Chen Qin (AAAI, 2021)

Semantic Concentration for Domain Adaptation. - Shuang Li 008; Mixue Xie; Fangrui Lv; Chi Harold Liu; Jian Liang 002; Chen Qin; Wei Li 111 (ICCV, 2021)

Policy-Driven Attack: Learning to Query for Hard-label Black-box Adversarial Examples. - Ziang Yan; Yiwen Guo; Jian Liang 002; Changshui Zhang (ICLR, 2021)

Addressing Algorithmic Disparity and Performance Inconsistency in Federated Learning. - Sen Cui; Weishen Pan; Jian Liang 002; Changshui Zhang; Fei Wang 001 (NeurIPS, 2021)

Pareto Domain Adaptation. - Fangrui Lv; Jian Liang 002; Kaixiong Gong; Shuang Li 008; Chi Harold Liu; Han Li 005; Di Liu; Guoren Wang (NeurIPS, 2021)

Learning to Collaborate. - Sen Cui; Jian Liang 002; Weishen Pan; Kun Chen 002; Changshui Zhang; Fei Wang 001 (CoRR, 2021)

Fair and Consistent Federated Learning. - Sen Cui; Weishen Pan; Jian Liang 002; Changshui Zhang; Fei Wang 001 (CoRR, 2021)

Incentive Compatible Pareto Alignment for Multi-Source Large Graphs. - Jian Liang 002; Fangrui Lv; Di Liu; Zehui Dai; Xu Tian; Shuang Li 008; Fei Wang 001; Han Li 005 (CoRR, 2021)

Robust Few-Shot Learning for User-Provided Data. - Jiang Lu; Sheng Jin 007; Jian Liang 002; Changshui Zhang (IEEE Trans. Neural Networks Learn. Syst., 2021)

Dynamic Hypergraph Learning for Collaborative Filtering. - Chunyu Wei; Jian Liang 002; Bing Bai; Di Liu (CIKM, 2022)

Causality Inspired Representation Learning for Domain Generalization. - Fangrui Lv; Jian Liang 002; Shuang Li 008; Bin Zang; Chi Harold Liu; Ziteng Wang; Di Liu (CVPR, 2022)

ACE: A Coarse-to-Fine Learning Framework for Reliable Representation Learning Against Label Noise. - Chenbin Zhang; Xiangli Yang; Jian Liang 002; Bing Bai; Kun Bai; Irwin King; Zenglin Xu (IJCNN, 2022)

Collaboration Equilibrium in Federated Learning. - Sen Cui; Jian Liang 002; Weishen Pan; Kun Chen 002; Changshui Zhang; Fei Wang 001 (KDD, 2022)

Synergy-of-Experts: Collaborate to Improve Adversarial Robustness. - Sen Cui; Jingfeng Zhang; Jian Liang 002; Bo Han 003; Masashi Sugiyama; Changshui Zhang (NeurIPS, 2022)

Adversarial Filtering Modeling on Long-term User Behavior Sequences for Click-Through Rate Prediction. - Xiaochen Li; Jian Liang 002; Xialong Liu; Yu Zhang (SIGIR, 2022)

Adversarial Filtering Modeling on Long-term User Behavior Sequences for Click-Through Rate Prediction. - Xiaochen Li; Rui Zhong; Jian Liang 002; Xialong Liu; Yu Zhang (CoRR, 2022)

Model-Protected Multi-Task Learning. - Jian Liang 002; Ziqi Liu; Jiayu Zhou; Xiaoqian Jiang; Changshui Zhang; Fei Wang 001 (IEEE Trans. Pattern Anal. Mach. Intell., 2022)

Improving Generalization with Domain Convex Game. - Fangrui Lv; Jian Liang 002; Shuang Li 008; Jinming Zhang; Di Liu (CVPR, 2023)

Meta Graph Learning for Long-tail Recommendation. - Chunyu Wei; Jian Liang 002; Di Liu; Zehui Dai; Mang Li; Fei Wang 001 (KDD, 2023)

Meta-Reweighted Regularization for Unsupervised Domain Adaptation. - Shuang Li 008; Wenxuan Ma 001; Jinming Zhang; Chi Harold Liu; Jian Liang 002; Guoren Wang (IEEE Trans. Knowl. Data Eng., 2023)

Subjective Topic meets LLMs: Unleashing Comprehensive, Reflective and Creative Thinking through the Negation of Negation. - Fangrui Lv; Kaixiong Gong; Jian Liang 002; Xinyu Pang; Changshui Zhang (EMNLP, 2024)

CLAP: Collaborative Adaptation for Patchwork Learning. - Sen Cui; Abudukelimu Wuerkaixi; Weishen Pan; Jian Liang 002; Lei Fang; Changshui Zhang; Fei Wang 001 (ICLR, 2024)

Exploring Structured Semantic Priors Underlying Diffusion Score for Test-time Adaptation. - Mingjia Li 003; Shuang Li 008; Tongrui Su; Longhui Yuan; Jian Liang 002; Wei Li 111 (NeurIPS, 2024)

Weight Diffusion for Future: Learn to Generalize in Non-Stationary Environments. - Mixue Xie; Shuang Li 008; Binhui Xie; Chi Harold Liu; Jian Liang 002; Zixun Sun; Ke Feng; Chengwei Zhu (NeurIPS, 2024)

Multi-Epoch learning with Data Augmentation for Deep Click-Through Rate Prediction. - Zhongxiang Fan; Zhaocheng Liu; Jian Liang 002; Dongying Kong; Han Li 005; Peng Jiang 002; Shuang Li 008; Kun Gai (CoRR, 2024)

From Local Details to Global Context: Advancing Vision-Language Models with Attention-Based Selection. - Lincan Cai; Jingxuan Kang; Shuang Li 008; Wenxuan Ma 001; Binhui Xie; Zhida Qin; Jian Liang 002 (CoRR, 2025)

Learning Time-Aware Causal Representation for Model Generalization in Evolving Domains. - Zhuo He; Shuang Li 008; Wenze Song; Longhui Yuan; Jian Liang 002; Han Li 005; Kun Gai (CoRR, 2025)