Sublinear Dual Coordinate Ascent for Regularized Loss Minimization. - Liu Liu 014; Dacheng Tao (ICDM, 2016)

Duality-free Methods for Stochastic Composition Optimization. - Liu Liu 014; Ji Liu 002; Dacheng Tao (CoRR, 2017)

Diversified dictionaries for multi-instance learning. - Maoying Qiao; Liu Liu 014; Jun Yu 002; Chang Xu 002; Dacheng Tao (Pattern Recognit., 2017)

Label Propagation via Teaching-to-Learn and Learning-to-Teach. - Chen Gong 002; Dacheng Tao; Wei Liu 005; Liu Liu 014; Jie Yang 002 (IEEE Trans. Neural Networks Learn. Syst., 2017)

Stochastic Zeroth-order Optimization via Variance Reduction method. - Liu Liu 014; Minhao Cheng; Cho-Jui Hsieh; Dacheng Tao (CoRR, 2018)

Stochastically Controlled Stochastic Gradient for the Convex and Non-convex Composition problem. - Liu Liu 014; Ji Liu 002; Cho-Jui Hsieh; Dacheng Tao (CoRR, 2018)

Stochastic Second-order Methods for Non-convex Optimization with Inexact Hessian and Gradient. - Liu Liu 014; Xuanqing Liu; Cho-Jui Hsieh; Dacheng Tao (CoRR, 2018)

GoDec+: Fast and Robust Low-Rank Matrix Decomposition Based on Maximum Correntropy. - Kailing Guo; Liu Liu 014; Xiangmin Xu; Dong Xu 001; Dacheng Tao (IEEE Trans. Neural Networks Learn. Syst., 2018)

Quantum algorithm for finding the negative curvature direction in non-convex optimization. - Kaining Zhang; Min-Hsiu Hsieh; Liu Liu 014; Dacheng Tao (CoRR, 2019)

The Double-Accelerated Stochastic Method for Regularized Empirical Risk Minimization. - Liu Liu 014; Dacheng Tao (IEEE Trans. Emerg. Top. Comput. Intell., 2019)

Dualityfree Methods for Stochastic Composition Optimization. - Liu Liu 014; Ji Liu 002; Dacheng Tao (IEEE Trans. Neural Networks Learn. Syst., 2019)

Deep Streaming Label Learning. - Zhen Wang 030; Liu Liu 014; Dacheng Tao (ICML, 2020)

Multi-label Few-shot Learning with Semantic Inference (Student Abstract). - Zhen Wang 030; Yiqun Duan; Liu Liu 014; Dacheng Tao (AAAI, 2021)

Adaptive Curriculum Learning. - Yajing Kong; Liu Liu 014; Jun Wang 002; Dacheng Tao (ICCV, 2021)

Contrastive Graph Poisson Networks: Semi-Supervised Learning with Extremely Limited Labels. - Sheng Wan; Yibing Zhan; Liu Liu 014; Baosheng Yu; Shirui Pan; Chen Gong 002 (NeurIPS, 2021)

A spatial structural similarity triplet loss for auxiliary vehicle re-identification. - Jianqing Zhu; Liu Liu 014; Xiaobin Zhu 001; Huanqiang Zeng (Sci. China Inf. Sci., 2021)

CAA : Channelized Axial Attention for Semantic Segmentation. - Ye Huang; Wenjing Jia; Xiangjian He; Liu Liu 014; Yuxin Li; Dacheng Tao (CoRR, 2021)

SkipNode: On Alleviating Over-smoothing for Deep Graph Convolutional Networks. - Weigang Lu; Yibing Zhan; Ziyu Guan; Liu Liu 014; Baosheng Yu; Wei Zhao 019; Yaming Yang 002; Dacheng Tao (CoRR, 2021)

Solving Jigsaw Puzzles via Nonconvex Quadratic Programming With the Projected Power Method. - Fang Yan 003; Yuanjie Zheng; Jinyu Cong; Liu Liu 014; Dacheng Tao; Sujuan Hou (IEEE Trans. Multim., 2021)

Continual Learning through Retrieval and Imagination. - Zhen Wang 030; Liu Liu 014; Yiqun Duan; Dacheng Tao (AAAI, 2022)

Resistance Training Using Prior Bias: Toward Unbiased Scene Graph Generation. - Chao Chen; Yibing Zhan; Baosheng Yu; Liu Liu 014; Yong Luo 002; Bo Du 001 (AAAI, 2022)

Channelized Axial Attention - considering Channel Relation within Spatial Attention for Semantic Segmentation. - Ye Huang; Di Kang; Wenjing Jia; Liu Liu 014; Xiangjian He (AAAI, 2022)

Continual Learning with Lifelong Vision Transformer. - Zhen Wang 030; Liu Liu 014; Yiqun Duan; Yajing Kong; Dacheng Tao (CVPR, 2022)

Text-to-Image Synthesis based on Object-Guided Joint-Decoding Transformer. - Fuxiang Wu; Liu Liu 014; Fusheng Hao; Fengxiang He; Jun Cheng 002 (CVPR, 2022)

Balancing Stability and Plasticity Through Advanced Null Space in Continual Learning. - Yajing Kong; Liu Liu 014; Zhen Wang 030; Dacheng Tao (ECCV (26), 2022)

Online Continual Learning with Contrastive Vision Transformer. - Zhen Wang 030; Liu Liu 014; Yajing Kong; Jiaxian Guo; Dacheng Tao (ECCV (20), 2022)

UMIX: Improving Importance Weighting for Subpopulation Shift via Uncertainty-Aware Mixup. - Zongbo Han; Zhipeng Liang; Fan Yang 081; Liu Liu 014; Lanqing Li; Yatao Bian; Peilin Zhao; Bingzhe Wu; Changqing Zhang; Jianhua Yao 001 (NeurIPS, 2022)

Escaping from the Barren Plateau via Gaussian Initializations in Deep Variational Quantum Circuits. - Kaining Zhang; Liu Liu 014; Min-Hsiu Hsieh; Dacheng Tao (NeurIPS, 2022)

Dual-branch Density Ratio Estimation for Signed Network Embedding. - Pinghua Xu; Yibing Zhan; Liu Liu 014; Baosheng Yu; Bo Du 001; Jia Wu 001; Wenbin Hu 001 (WWW, 2022)

Robust Imitation Learning from Corrupted Demonstrations. - Liu Liu 014; Ziyang Tang; Lanqing Li; Dijun Luo (CoRR, 2022)

Gaussian initializations help deep variational quantum circuits escape from the barren plateau. - Kaining Zhang; Min-Hsiu Hsieh; Liu Liu 014; Dacheng Tao (CoRR, 2022)

Exploring High-Order Structure for Robust Graph Structure Learning. - Guangqian Yang; Yibing Zhan; Jinlong Li; Baosheng Yu; Liu Liu 014; Fengxiang He (CoRR, 2022)

Robust Offline Reinforcement Learning with Gradient Penalty and Constraint Relaxation. - Chengqian Gao; Ke Xu; Liu Liu 014; Deheng Ye; Peilin Zhao; Zhiqiang Xu 003 (CoRR, 2022)

Variance Reduced Methods for Non-Convex Composition Optimization. - Liu Liu 014; Ji Liu 002; Dacheng Tao (IEEE Trans. Pattern Anal. Mach. Intell., 2022)

Imposing Semantic Consistency of Local Descriptors for Few-Shot Learning. - Jun Cheng 002; Fusheng Hao; Liu Liu 014; Dacheng Tao (IEEE Trans. Image Process., 2022)

Reject Decoding via Language-Vision Models for Text-to-Image Synthesis. - Fuxiang Wu; Liu Liu 014; Fusheng Hao; Fengxiang He; Lei Wang 018; Jun Cheng 002 (AAAI, 2023)

Class-Aware Patch Embedding Adaptation for Few-Shot Image Classification. - Fusheng Hao; Fengxiang He; Liu Liu 014; Fuxiang Wu; Dacheng Tao; Jun Cheng 002 (ICCV, 2023)

BEEF: Bi-Compatible Class-Incremental Learning via Energy-Based Expansion and Fusion. - Fu-Yun Wang; Da-Wei Zhou 001; Liu Liu 014; Han-Jia Ye; Yatao Bian; De-Chuan Zhan; Peilin Zhao (ICLR, 2023)

Deploying Offline Reinforcement Learning with Human Feedback. - Ziniu Li; Ke Xu; Liu Liu 014; Lanqing Li; Deheng Ye; Peilin Zhao (CoRR, 2023)

Reweighted Mixup for Subpopulation Shift. - Zongbo Han; Zhipeng Liang; Fan Yang 081; Liu Liu 014; Lanqing Li; Yatao Bian; Peilin Zhao; Qinghua Hu; Bingzhe Wu; Changqing Zhang; Jianhua Yao 001 (CoRR, 2023)

Differentiable Frank-Wolfe Optimization Layer. - Zixuan Liu 002; Liu Liu 014; Xueqian Wang 001; Peilin Zhao (CoRR, 2023)

Stochastic Optimization for Non-convex Problem with Inexact Hessian Matrix, Gradient, and Function. - Liu Liu 014; Xuanqing Liu; Cho-Jui Hsieh; Dacheng Tao (CoRR, 2023)

Attribute-Image Person Re-identification via Modal-Consistent Metric Learning. - Jianqing Zhu; Liu Liu 014; Yibing Zhan; Xiaobin Zhu 001; Huanqiang Zeng; Dacheng Tao (Int. J. Comput. Vis., 2023)

Dynamics Adapted Imitation Learning. - Zixuan Liu 002; Liu Liu 014; Bingzhe Wu; Lanqing Li; Xueqian Wang 001; Bo Yuan 008; Peilin Zhao (Trans. Mach. Learn. Res., 2023)

Mixer-Based Semantic Spread for Few-Shot Learning. - Jun Cheng 002; Fusheng Hao; Fengxiang He; Liu Liu 014; Qieshi Zhang (IEEE Trans. Multim., 2023)

InDecGAN: Learning to Generate Complex Images From Captions via Independent Object-Level Decomposition and Enhancement. - Jun Cheng 002; Fuxiang Wu; Liu Liu 014; Qieshi Zhang; Leszek Rutkowski; Dacheng Tao (IEEE Trans. Multim., 2023)

Language-Based Image Manipulation Built on Language-Guided Ranking. - Fuxiang Wu; Liu Liu 014; Fusheng Hao; Fengxiang He; Jun Cheng 002 (IEEE Trans. Multim., 2023)

The Visual Footsteps Planning System for Exoskeleton Robots Under Complex Terrain. - Xinyu Wu 001; Jinke Li; Liu Liu 014; Dacheng Tao (IEEE Trans. Syst. Man Cybern. Syst., 2023)

On the Guaranteed Almost Equivalence Between Imitation Learning From Observation and Demonstration. - Zhihao Cheng; Liu Liu 014; Aishan Liu; Hao Sun 019; Meng Fang; Dacheng Tao (IEEE Trans. Neural Networks Learn. Syst., 2023)

Stochastically Controlled Compositional Gradient for Composition Problems. - Liu Liu 014; Ji Liu 002; Cho-Jui Hsieh; Dacheng Tao (IEEE Trans. Neural Networks Learn. Syst., 2023)

Generalised Watson Distribution on the Hypersphere with Applications to Clustering. - Stephen J. Maybank; Liu Liu 014; Dacheng Tao (J. Math. Imaging Vis., 2023)

Trust-Region Adaptive Frequency for Online Continual Learning. - Yajing Kong; Liu Liu 014; Maoying Qiao; Zhen Wang 030; Dacheng Tao (Int. J. Comput. Vis., 2023)

On exploring node-feature and graph-structure diversities for node drop graph pooling. - Chuang Liu 008; Yibing Zhan; Baosheng Yu; Liu Liu 014; Bo Du 001; Wenbin Hu 001; Tongliang Liu (Neural Networks, 2023)

Prescribed Safety Performance Imitation Learning From a Single Expert Dataset. - Zhihao Cheng; Li Shen 008; Miaoxi Zhu; Jiaxian Guo; Meng Fang; Liu Liu 014; Bo Du 001; Dacheng Tao (IEEE Trans. Pattern Anal. Mach. Intell., 2023)

SIN: Semantic Inference Network for Few-Shot Streaming Label Learning. - Zhen Wang 030; Liu Liu 014; Yiqun Duan; Dacheng Tao (IEEE Trans. Neural Networks Learn. Syst., 2023)

DFWLayer: Differentiable Frank-Wolfe Optimization Layer. - Zixuan Liu 002; Liu Liu 014; Xueqian Wang 001; Peilin Zhao (Tiny Papers @ ICLR, 2024)

Pareto Deep Long-Tailed Recognition: A Conflict-Averse Solution. - Zhipeng Zhou; Liu Liu 014; Peilin Zhao; Wei Gong 001 (ICLR, 2024)

Step-On-Feet Tuning: Scaling Self-Alignment of LLMs via Bootstrapping. - Haoyu Wang 003; Guozheng Ma; Ziqiao Meng; Zeyu Qin; Li Shen 008; Zhong Zhang; Bingzhe Wu; Liu Liu 014; Yatao Bian; Tingyang Xu; Xueqian Wang 001; Peilin Zhao (CoRR, 2024)

The curse of random quantum data. - Kaining Zhang; Junyu Liu; Liu Liu 014; Liang Jiang; Min-Hsiu Hsieh; Dacheng Tao (CoRR, 2024)

Cross-modal group-relation optimization for visible-infrared person re-identification. - Jianqing Zhu; Hanxiao Wu; Yutao Chen; Heng Xu; Yuqing Fu; Huanqiang Zeng; Liu Liu 014; Zhen Lei 001 (Neural Networks, 2024)

Modality-Consistent Attention for Visible-Infrared Vehicle Re-Identification. - Qianqian Zhao; Jiajun Su; Jianqing Zhu; Liu Liu 014; Huanqiang Zeng (IEEE Signal Process. Lett., 2024)

SkipNode: On Alleviating Performance Degradation for Deep Graph Convolutional Networks. - Weigang Lu; Yibing Zhan; Binbin Lin; Ziyu Guan; Liu Liu 014; Baosheng Yu; Wei Zhao 019; Yaming Yang 002; Dacheng Tao (IEEE Trans. Knowl. Data Eng., 2024)

Overcoming Catastrophic Forgetting in Continual Learning by Exploring Eigenvalues of Hessian Matrix. - Yajing Kong; Liu Liu 014; Huanhuan Chen; Janusz Kacprzyk; Dacheng Tao (IEEE Trans. Neural Networks Learn. Syst., 2024)

HDT: Hierarchical Discrete Transformer for Multivariate Time Series Forecasting. - Shibo Feng; Peilin Zhao; Liu Liu 014; Pengcheng Wu; Zhiqi Shen 001 (AAAI, 2025)

SkipNode: On Alleviating Performance Degradation for Deep Graph Convolutional Networks (Extended Abstract). - Weigang Lu; Yibing Zhan; Binbin Lin; Ziyu Guan; Liu Liu 014; Baosheng Yu; Wei Zhao 019; Yaming Yang 002; Dacheng Tao (ICDE, 2025)

Memory-augmented shuffled meta learning for visible-infrared person re-identification. - Hanxiao Wu; Yutao Chen; Yi Xie; Jianqing Zhu; Liu Liu 014; Huanqiang Zeng (Neural Networks, 2025)

Textual Embeddings are Good Class-Aware Visual Prompts for Adapting Vision-Language Models. - Fusheng Hao; Liu Liu 014; Fuxiang Wu; Qieshi Zhang; Jun Cheng 002 (IEEE Signal Process. Lett., 2025)

Stochastic Optimization for Nonconvex Problem With Inexact Hessian Matrix, Gradient, and Function. - Liu Liu 014; Xuanqing Liu; Cho-Jui Hsieh; Dacheng Tao (IEEE Trans. Neural Networks Learn. Syst., 2025)

Principled Data Selection for Alignment: The Hidden Risks of Difficult Examples. - Chengqian Gao; Haonan Li; Liu Liu 014; Zeke Xie; Peilin Zhao; Zhiqiang Xu 003 (CoRR, 2025)

Injecting Imbalance Sensitivity for Multi-Task Learning. - Zhipeng Zhou; Liu Liu 014; Peilin Zhao; Wei Gong 001 (CoRR, 2025)

Class-Irrelevant Feature Removal for Few-Shot Image Classification. - Fusheng Hao; Liu Liu 014; Fuxiang Wu; Qieshi Zhang; Jun Cheng 002 (IEEE Trans. Neural Networks Learn. Syst., 2025)

SIGMA: Refining Large Language Model Reasoning via Sibling-Guided Monte Carlo Augmentation. - Yanwei Ren; Haotian Zhang; Fuxiang Wu; Jiayan Qiu; Jiaxing Huang; Baosheng Yu; Liu Liu 014 (CoRR, 2025)

LARGO: Low-Rank Regulated Gradient Projection for Robust Parameter Efficient Fine-Tuning. - Haotian Zhang; Liu Liu 014; Baosheng Yu; Jiayan Qiu; Yanwei Ren; Xianglong Liu 001 (CoRR, 2025)

Re-Initialization Token Learning for Tool-Augmented Large Language Models. - Chenghao Li; Liu Liu 014; Baosheng Yu; Jiayan Qiu; Yibing Zhan (CoRR, 2025)

Instruction Learning Paradigms: A Dual Perspective on White-box and Black-box LLMs. - Yanwei Ren; Liu Liu 014; Baosheng Yu; Jiayan Qiu; Quan Chen (CoRR, 2025)

Gradient-based Fine-Tuning through Pre-trained Model Regularization. - Xuanbo Liu; Liu Liu 014; Fuxiang Wu; Fusheng Hao; Xianglong Liu 001 (CoRR, 2025)