Gong, Tieliang

23 publications

ICML 2025 Exactly Tight Information-Theoretic Generalization Bounds via Binary Jensen-Shannon Divergence Yuxin Dong, Haoran Guo, Tieliang Gong, Wen Wen, Chen Li

ICML 2025 InfoSAM: Fine-Tuning the Segment Anything Model from an Information-Theoretic Perspective Yuanhong Zhang, Muyao Yuan, Weizhan Zhang, Tieliang Gong, Wen Wen, Jiangyong Ying, Weijie Shi

MLJ 2025 Leveraging Differentiable NAS and Abstract Genetic Algorithms for Optimizing On-Mobile VSR Performance Xuncheng Liu, Weizhan Zhang, Tieliang Gong, Caixia Yan, Rui Li

CVPR 2025 Rectified Diffusion Guidance for Conditional Generation Mengfei Xia, Nan Xue, Yujun Shen, Ran Yi, Tieliang Gong, Yong-Jin Liu

AAAI 2025 SpotActor: Training-Free Layout-Controlled Consistent Image Generation Jiahao Wang, Caixia Yan, Weizhan Zhang, Haonan Lin, Mengmeng Wang, Guang Dai, Tieliang Gong, Hao Sun, Jingdong Wang

ICLR 2025 Towards Generalization Bounds of GCNs for Adversarially Robust Node Classification Wen Wen, Han Li, Tieliang Gong, Hong Chen

IJCAI 2025 Trajectory-Dependent Generalization Bounds for Pairwise Learning with Φ-Mixing Samples Liyuan Liu, Hong Chen, Weifu Li, Tieliang Gong, Hao Deng, Yulong Wang

NeurIPS 2024 Accelerating Non-Maximum Suppression: A Graph Theory Perspective King-Siong Si, Lu Sun, Weizhan Zhang, Tieliang Gong, Jiahao Wang, Jiang Liu, Hao Sun

IJCAI 2024 Fine-Grained Analysis of Stability and Generalization for Stochastic Bilevel Optimization Xuelin Zhang, Hong Chen, Bin Gu, Tieliang Gong, Feng Zheng

NeurIPS 2024 OneActor: Consistent Subject Generation via Cluster-Conditioned Guidance Jiahao Wang, Caixia Yan, Haonan Lin, Weizhan Zhang, Mengmeng Wang, Tieliang Gong, Guang Dai, Hao Sun

ICLR 2024 Rethinking Information-Theoretic Generalization: Loss Entropy Induced PAC Bounds Yuxin Dong, Tieliang Gong, Hong Chen, Shujian Yu, Chen Li

ICML 2024 Towards Generalization Beyond Pointwise Learning: A Unified Information-Theoretic Perspective Yuxin Dong, Tieliang Gong, Hong Chen, Zhongjiang He, Mengxiang Li, Shuangyong Song, Chen Li

IJCAI 2024 Towards Sharper Generalization Bounds for Adversarial Contrastive Learning Wen Wen, Han Li, Tieliang Gong, Hong Chen

CVPR 2024 ViLa-MIL: Dual-Scale Vision-Language Multiple Instance Learning for Whole Slide Image Classification Jiangbo Shi, Chen Li, Tieliang Gong, Yefeng Zheng, Huazhu Fu

AAAI 2023 On the Stability and Generalization of Triplet Learning Jun Chen, Hong Chen, Xue Jiang, Bin Gu, Weifu Li, Tieliang Gong, Feng Zheng

AAAI 2023 Robust and Fast Measure of Information via Low-Rank Representation Yuxin Dong, Tieliang Gong, Shujian Yu, Hong Chen, Chen Li

ICML 2023 Tilted Sparse Additive Models Yingjie Wang, Hong Chen, Weifeng Liu, Fengxiang He, Tieliang Gong, Youcheng Fu, Dacheng Tao

IJCAI 2023 Understanding the Generalization Ability of Deep Learning Algorithms: A Kernelized Rényi's Entropy Perspective Yuxin Dong, Tieliang Gong, Hong Chen, Chen Li

AAAI 2022 Error-Based Knockoffs Inference for Controlled Feature Selection Xuebin Zhao, Hong Chen, Yingjie Wang, Weifu Li, Tieliang Gong, Yulong Wang, Feng Zheng

AAAI 2022 Regularized Modal Regression on Markov-Dependent Observations: A Theoretical Assessment Tieliang Gong, Yuxin Dong, Hong Chen, Wei Feng, Bo Dong, Chen Li

NeurIPS 2020 Multi-Task Additive Models for Robust Estimation and Automatic Structure Discovery Yingjie Wang, Hong Chen, Feng Zheng, Chen Xu, Tieliang Gong, Yanhong Chen

AAAI 2020 Robust Gradient-Based Markov Subsampling Tieliang Gong, Quanhan Xi, Chen Xu

AAAI 2018 Margin Based PU Learning Tieliang Gong, Guangtao Wang, Jieping Ye, Zongben Xu, Ming Lin