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ORCIDJian Liang 0001
Person information
- affiliation: Chinese Academy of Sciences, Institute of Automation, Center for Research on Intelligent Perception and Computing, State Key Laboratory of Multimodal Artificial Intelligence Systems (MAIS), Beijing, China
- affiliation: University of Chinese Academy of Sciences, School of Artificial Intelligence, Beijing, China
- affiliation (2019 - 2021): National University of Singapore, Department of Electrical and Computer Engineering, Singapore
Other persons with the same name
- Jian Liang — disambiguation page
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2020 – today
- 2024
[j15]Yujun Shi
, Jian Liang, Wenqing Zhang, Chuhui Xue, Vincent Y. F. Tan, Song Bai:
Understanding and Mitigating Dimensional Collapse in Federated Learning. IEEE Trans. Pattern Anal. Mach. Intell. 46(5): 2936-2949 (2024)- [j14]Yuhe Ding, Jian Liang, Bo Jiang, Aihua Zheng, Ran He:
MAPS: A Noise-Robust Progressive Learning Approach for Source-Free Domain Adaptive Keypoint Detection. IEEE Trans. Circuits Syst. Video Technol. 34(3): 1376-1387 (2024) - [c46]Jiyang Guan, Jian Liang, Ran He:
Backdoor Defense via Test-Time Detecting and Repairing. CVPR 2024: 24564-24573 - [c45]Yanbo Wang, Jian Liang, Ran He:
Towards Eliminating Hard Label Constraints in Gradient Inversion Attacks. ICLR 2024 - [c44]Zhengbo Wang, Jian Liang, Lijun Sheng, Ran He, Zilei Wang, Tieniu Tan:
A Hard-to-Beat Baseline for Training-free CLIP-based Adaptation. ICLR 2024 - [c43]Jian Liang, Lijun Sheng, Zhengbo Wang, Ran He, Tieniu Tan:
Realistic Unsupervised CLIP Fine-tuning with Universal Entropy Optimization. ICML 2024 - [c42]Zhengbo Wang, Jian Liang, Ran He, Zilei Wang, Tieniu Tan:
Connecting the Dots: Collaborative Fine-tuning for Black-Box Vision-Language Models. ICML 2024 - [i56]Kuangpu Guo, Yuhe Ding, Jian Liang, Ran He, Zilei Wang, Tieniu Tan:
Not all Minorities are Equal: Empty-Class-Aware Distillation for Heterogeneous Federated Learning. CoRR abs/2401.02329 (2024) - [i55]Lijun Sheng, Jian Liang, Ran He, Zilei Wang, Tieniu Tan:
Can We Trust the Unlabeled Target Data? Towards Backdoor Attack and Defense on Model Adaptation. CoRR abs/2401.06030 (2024) - [i54]Yanbo Wang, Jian Liang, Ran He:
Towards Eliminating Hard Label Constraints in Gradient Inversion Attacks. CoRR abs/2402.03124 (2024) - [i53]Zhengbo Wang, Jian Liang, Ran He, Zilei Wang, Tieniu Tan:
Connecting the Dots: Collaborative Fine-tuning for Black-Box Vision-Language Models. CoRR abs/2402.04050 (2024) - [i52]Zhengbo Wang, Jian Liang, Lijun Sheng, Ran He, Zilei Wang, Tieniu Tan:
A Hard-to-Beat Baseline for Training-free CLIP-based Adaptation. CoRR abs/2402.04087 (2024) - [i51]Yuhe Ding, Bo Jiang, Aijing Yu, Aihua Zheng, Jian Liang:
Which Model to Transfer? A Survey on Transferability Estimation. CoRR abs/2402.15231 (2024) - [i50]Jian Jia, Yipei Wang, Yan Li, Honggang Chen, Xuehan Bai, Zhaocheng Liu, Jian Liang, Quan Chen, Han Li, Peng Jiang, Kun Gai:
Knowledge Adaptation from Large Language Model to Recommendation for Practical Industrial Application. CoRR abs/2405.03988 (2024) - [i49]Zhongxiang Fan, Zhaocheng Liu, Jian Liang, Dongying Kong, Han Li, Peng Jiang, Shuang Li, Kun Gai:
Multi-Epoch learning with Data Augmentation for Deep Click-Through Rate Prediction. CoRR abs/2407.01607 (2024) - [i48]Shuo Lu, Yingsheng Wang, Lijun Sheng, Aihua Zheng, Lingxiao He, Jian Liang:
Recent Advances in OOD Detection: Problems and Approaches. CoRR abs/2409.11884 (2024) - 2023
- [j13]Yuhe Ding, Lijun Sheng, Jian Liang, Aihua Zheng, Ran He:
ProxyMix: Proxy-based Mixup training with label refinery for source-free domain adaptation. Neural Networks 167: 92-103 (2023) - [j12]Ziming Yang, Jian Liang, Yuting Xu, Xiaoyu Zhang, Ran He:
Masked Relation Learning for DeepFake Detection. IEEE Trans. Inf. Forensics Secur. 18: 1696-1708 (2023) - [j11]Shuang Li, Wenxuan Ma, Jinming Zhang, Chi Harold Liu, Jian Liang, Guoren Wang:
Meta-Reweighted Regularization for Unsupervised Domain Adaptation. IEEE Trans. Knowl. Data Eng. 35(3): 2781-2795 (2023) - [c41]Junchi Yu, Jian Liang, Ran He:
Mind the Label Shift of Augmentation-based Graph OOD Generalization. CVPR 2023: 11620-11630 - [c40]Fangrui Lv, Jian Liang, Shuang Li, Jinming Zhang, Di Liu:
Improving Generalization with Domain Convex Game. CVPR 2023: 24315-24324 - [c39]Yuhe Ding, Jian Liang, Jie Cao, Aihua Zheng, Ran He:
Modify: Model-Driven Face Stylization Without Style Images. ICASSP 2023: 1-5 - [c38]Zhengbo Wang, Jian Liang, Zilei Wang, Tieniu Tan:
Notice of Removal: Exploiting Semantic Attributes for Transductive Zero-Shot Learning. ICASSP 2023: 1-5 - [c37]Yuxi Wang, Jian Liang, Jun Xiao, Shuqi Mei, Yuran Yang, Zhaoxiang Zhang:
Informative Data Mining for One-shot Cross-Domain Semantic Segmentation. ICCV 2023: 1064-1074 - [c36]Yuting Xu, Jian Liang, Gengyun Jia, Ziming Yang, Yanhao Zhang, Ran He:
TALL: Thumbnail Layout for Deepfake Video Detection. ICCV 2023: 22601-22611 - [c35]Yujun Shi, Jian Liang, Wenqing Zhang, Vincent Y. F. Tan, Song Bai:
Towards Understanding and Mitigating Dimensional Collapse in Heterogeneous Federated Learning. ICLR 2023 - [c34]Yifan Zhang, Xue Wang, Jian Liang, Zhang Zhang, Liang Wang, Rong Jin, Tieniu Tan:
Free Lunch for Domain Adversarial Training: Environment Label Smoothing. ICLR 2023 - [c33]Chunyu Wei, Jian Liang, Di Liu, Zehui Dai, Mang Li, Fei Wang:
Meta Graph Learning for Long-tail Recommendation. KDD 2023: 2512-2522 - [c32]Kaiwei Zhang, Junchi Yu, Haichao Shi, Jian Liang, Xiaoyu Zhang:
Rumor Detection with Diverse Counterfactual Evidence. KDD 2023: 3321-3331 - [c31]Yi-Fan Zhang, Jindong Wang, Jian Liang, Zhang Zhang, Baosheng Yu, Liang Wang, Dacheng Tao, Xing Xie:
Domain-Specific Risk Minimization for Domain Generalization. KDD 2023: 3409-3421 - [i47]Boqiang Xu, Lingxiao He, Jian Liang, Zhenan Sun:
Learning Feature Recovery Transformer for Occluded Person Re-identification. CoRR abs/2301.01879 (2023) - [i46]Yifan Zhang, Xue Wang, Jian Liang, Zhang Zhang, Liang Wang, Rong Jin, Tieniu Tan:
Free Lunch for Domain Adversarial Training: Environment Label Smoothing. CoRR abs/2302.00194 (2023) - [i45]Yuhe Ding, Jian Liang, Bo Jiang, Aihua Zheng, Ran He:
MAPS: A Noise-Robust Progressive Learning Approach for Source-Free Domain Adaptive Keypoint Detection. CoRR abs/2302.04589 (2023) - [i44]Yuhe Ding, Jian Liang, Jie Cao, Aihua Zheng, Ran He:
MODIFY: Model-driven Face Stylization without Style Images. CoRR abs/2303.09831 (2023) - [i43]Zhengbo Wang, Jian Liang, Zilei Wang, Tieniu Tan:
Exploiting Semantic Attributes for Transductive Zero-Shot Learning. CoRR abs/2303.09849 (2023) - [i42]Lijun Sheng, Jian Liang, Ran He, Zilei Wang, Tieniu Tan:
AdaptGuard: Defending Against Universal Attacks for Model Adaptation. CoRR abs/2303.10594 (2023) - [i41]Puning Yang, Jian Liang, Jie Cao, Ran He:
AUTO: Adaptive Outlier Optimization for Online Test-Time OOD Detection. CoRR abs/2303.12267 (2023) - [i40]Fangrui Lv, Jian Liang, Shuang Li, Jinming Zhang, Di Liu:
Improving Generalization with Domain Convex Game. CoRR abs/2303.13297 (2023) - [i39]Junchi Yu, Jian Liang, Ran He:
Mind the Label Shift of Augmentation-based Graph OOD Generalization. CoRR abs/2303.14859 (2023) - [i38]Jian Liang, Ran He, Tieniu Tan:
A Comprehensive Survey on Test-Time Adaptation under Distribution Shifts. CoRR abs/2303.15361 (2023) - [i37]Yongcan Yu, Lijun Sheng, Ran He, Jian Liang:
Benchmarking Test-Time Adaptation against Distribution Shifts in Image Classification. CoRR abs/2307.03133 (2023) - [i36]Zhengbo Wang, Jian Liang, Ran He, Nan Xu, Zilei Wang, Tieniu Tan:
Improving Zero-Shot Generalization for CLIP with Synthesized Prompts. CoRR abs/2307.07397 (2023) - [i35]Yuting Xu, Jian Liang, Gengyun Jia, Ziming Yang, Yanhao Zhang, Ran He:
TALL: Thumbnail Layout for Deepfake Video Detection. CoRR abs/2307.07494 (2023) - [i34]Kaiwei Zhang, Junchi Yu, Haichao Shi, Jian Liang, Xiaoyu Zhang:
Rumor Detection with Diverse Counterfactual Evidence. CoRR abs/2307.09296 (2023) - [i33]Jiyang Guan, Jian Liang, Ran He:
Test-Time Adaptation for Backdoor Defense. CoRR abs/2308.06107 (2023) - [i32]Jian Liang, Lijun Sheng, Zhengbo Wang, Ran He, Tieniu Tan:
Towards Realistic Unsupervised Fine-tuning with CLIP. CoRR abs/2308.12919 (2023) - [i31]Yuxi Wang, Jian Liang, Jun Xiao, Shuqi Mei, Yuran Yang, Zhaoxiang Zhang:
Informative Data Mining for One-Shot Cross-Domain Semantic Segmentation. CoRR abs/2309.14241 (2023) - [i30]Yuhe Ding, Bo Jiang, Lijun Sheng, Aihua Zheng, Jian Liang:
Unleashing the power of Neural Collapse for Transferability Estimation. CoRR abs/2310.05754 (2023) - 2022
- [j10]Jian Liang, Dapeng Hu, Yunbo Wang, Ran He, Jiashi Feng:
Source Data-Absent Unsupervised Domain Adaptation Through Hypothesis Transfer and Labeling Transfer. IEEE Trans. Pattern Anal. Mach. Intell. 44(11): 8602-8617 (2022) - [j9]Ziming Yang, Jian Liang, Chaoyou Fu, Mandi Luo, Xiaoyu Zhang:
Heterogeneous Face Recognition via Face Synthesis With Identity-Attribute Disentanglement. IEEE Trans. Inf. Forensics Secur. 17: 1344-1358 (2022) - [j8]Boqiang Xu, Lingxiao He, Jian Liang, Zhenan Sun:
Learning Feature Recovery Transformer for Occluded Person Re-Identification. IEEE Trans. Image Process. 31: 4651-4662 (2022) - [c30]Jian Liang, Dapeng Hu, Jiashi Feng, Ran He:
DINE: Domain Adaptation from Single and Multiple Black-box Predictors. CVPR 2022: 7993-8003 - [c29]Fangrui Lv, Jian Liang, Shuang Li, Bin Zang, Chi Harold Liu, Ziteng Wang, Di Liu:
Causality Inspired Representation Learning for Domain Generalization. CVPR 2022: 8036-8046 - [c28]Yujun Shi, Kuangqi Zhou, Jian Liang, Zihang Jiang, Jiashi Feng, Philip H. S. Torr, Song Bai, Vincent Y. F. Tan:
Mimicking the Oracle: An Initial Phase Decorrelation Approach for Class Incremental Learning. CVPR 2022: 16701-16710 - [c27]Boqiang Xu, Jian Liang, Lingxiao He, Zhenan Sun:
Mimic Embedding via Adaptive Aggregation: Learning Generalizable Person Re-identification. ECCV (14) 2022: 372-388 - [c26]Jiyang Guan, Jian Liang, Ran He:
Are You Stealing My Model? Sample Correlation for Fingerprinting Deep Neural Networks. NeurIPS 2022 - [c25]Chunyu Wei, Jian Liang, Di Liu, Fei Wang:
Contrastive Graph Structure Learning via Information Bottleneck for Recommendation. NeurIPS 2022 - [i29]Fangrui Lv, Jian Liang, Shuang Li, Bin Zang, Chi Harold Liu, Ziteng Wang, Di Liu:
Causality Inspired Representation Learning for Domain Generalization. CoRR abs/2203.14237 (2022) - [i28]Yuhe Ding, Lijun Sheng, Jian Liang, Aihua Zheng, Ran He:
ProxyMix: Proxy-based Mixup Training with Label Refinery for Source-Free Domain Adaptation. CoRR abs/2205.14566 (2022) - [i27]Ziming Yang, Jian Liang, Chaoyou Fu, Mandi Luo, Xiaoyu Zhang:
Heterogeneous Face Recognition via Face Synthesis with Identity-Attribute Disentanglement. CoRR abs/2206.04854 (2022) - [i26]Junchi Yu, Jian Liang, Ran He:
Finding Diverse and Predictable Subgraphs for Graph Domain Generalization. CoRR abs/2206.09345 (2022) - [i25]Yujun Shi, Jian Liang, Wenqing Zhang, Vincent Y. F. Tan, Song Bai:
Towards Understanding and Mitigating Dimensional Collapse in Heterogeneous Federated Learning. CoRR abs/2210.00226 (2022) - [i24]Jiyang Guan, Jian Liang, Ran He:
Are You Stealing My Model? Sample Correlation for Fingerprinting Deep Neural Networks. CoRR abs/2210.15427 (2022) - 2021
- [j7]Yunbo Wang, Xianfeng Ou, Jian Liang, Zhenan Sun:
Deep Semantic Reconstruction Hashing for Similarity Retrieval. IEEE Trans. Circuits Syst. Video Technol. 31(1): 387-400 (2021) - [j6]Dapeng Hu, Jian Liang, Qibin Hou, Hanshu Yan, Yunpeng Chen:
Adversarial Domain Adaptation With Prototype-Based Normalized Output Conditioner. IEEE Trans. Image Process. 30: 9359-9371 (2021) - [c24]Shuang Li, Fangrui Lv, Binhui Xie, Chi Harold Liu, Jian Liang, Chen Qin:
Bi-Classifier Determinacy Maximization for Unsupervised Domain Adaptation. AAAI 2021: 8455-8464 - [c23]Jian Liang, Dapeng Hu, Jiashi Feng:
Domain Adaptation With Auxiliary Target Domain-Oriented Classifier. CVPR 2021: 16632-16642 - [c22]Shuang Li, Mixue Xie, Fangrui Lv, Chi Harold Liu, Jian Liang, Chen Qin, Wei Li:
Semantic Concentration for Domain Adaptation. ICCV 2021: 9082-9091 - [c21]Bing Bai, Jian Liang, Guanhua Zhang, Hao Li, Kun Bai, Fei Wang:
Why Attentions May Not Be Interpretable? KDD 2021: 25-34 - [c20]Mi Luo, Fei Chen, Dapeng Hu, Yifan Zhang, Jian Liang, Jiashi Feng:
No Fear of Heterogeneity: Classifier Calibration for Federated Learning with Non-IID Data. NeurIPS 2021: 5972-5984 - [c19]Fangrui Lv, Jian Liang, Kaixiong Gong, Shuang Li, Chi Harold Liu, Han Li, Di Liu, Guoren Wang:
Pareto Domain Adaptation. NeurIPS 2021: 12917-12929 - [c18]Yifan Zhang, Bryan Hooi, Dapeng Hu, Jian Liang, Jiashi Feng:
Unleashing the Power of Contrastive Self-Supervised Visual Models via Contrast-Regularized Fine-Tuning. NeurIPS 2021: 29848-29860 - [i23]Yifan Zhang, Bryan Hooi, Dapeng Hu, Jian Liang, Jiashi Feng:
Unleashing the Power of Contrastive Self-Supervised Visual Models via Contrast-Regularized Fine-Tuning. CoRR abs/2102.06605 (2021) - [i22]Jian Liang, Dapeng Hu, Ran He, Jiashi Feng:
Distill and Fine-tune: Effective Adaptation from a Black-box Source Model. CoRR abs/2104.01539 (2021) - [i21]Mi Luo, Fei Chen, Dapeng Hu, Yifan Zhang, Jian Liang, Jiashi Feng:
No Fear of Heterogeneity: Classifier Calibration for Federated Learning with Non-IID Data. CoRR abs/2106.05001 (2021) - [i20]Yuxi Wang, Jian Liang, Zhaoxiang Zhang:
Give Me Your Trained Model: Domain Adaptive Semantic Segmentation without Source Data. CoRR abs/2106.11653 (2021) - [i19]Shuang Li, Mixue Xie, Fangrui Lv, Chi Harold Liu, Jian Liang, Chen Qin, Wei Li:
Semantic Concentration for Domain Adaptation. CoRR abs/2108.05720 (2021) - [i18]Jian Liang, Fangrui Lv, Di Liu, Zehui Dai, Xu Tian, Shuang Li, Fei Wang, Han Li:
Incentive Compatible Pareto Alignment for Multi-Source Large Graphs. CoRR abs/2112.02792 (2021) - [i17]Fangrui Lv, Jian Liang, Kaixiong Gong, Shuang Li, Chi Harold Liu, Han Li, Di Liu, Guoren Wang:
Pareto Domain Adaptation. CoRR abs/2112.04137 (2021) - [i16]Yujun Shi, Kuangqi Zhou, Jian Liang, Zihang Jiang, Jiashi Feng, Philip H. S. Torr, Song Bai, Vincent Y. F. Tan:
Mimicking the Oracle: An Initial Phase Decorrelation Approach for Class Incremental Learning. CoRR abs/2112.04731 (2021) - [i15]Jian Liang, Dapeng Hu, Jiashi Feng, Ran He:
UMAD: Universal Model Adaptation under Domain and Category Shift. CoRR abs/2112.08553 (2021) - [i14]Boqiang Xu, Jian Liang, Lingxiao He, Zhenan Sun:
META: Mimicking Embedding via oThers' Aggregation for Generalizable Person Re-identification. CoRR abs/2112.08684 (2021) - 2020
- [c17]Jian Liang, Yunbo Wang, Dapeng Hu, Ran He, Jiashi Feng:
A Balanced and Uncertainty-Aware Approach for Partial Domain Adaptation. ECCV (11) 2020: 123-140 - [c16]Jian Liang, Dapeng Hu, Jiashi Feng:
Do We Really Need to Access the Source Data? Source Hypothesis Transfer for Unsupervised Domain Adaptation. ICML 2020: 6028-6039 - [c15]Jian Liang, Bing Bai, Yuren Cao, Kun Bai, Fei Wang:
Adversarial Infidelity Learning for Model Interpretation. KDD 2020: 286-296 - [c14]Junqi Zhang, Bing Bai, Ye Lin, Jian Liang, Kun Bai, Fei Wang:
General-Purpose User Embeddings based on Mobile App Usage. KDD 2020: 2831-2840 - [i13]Jian Liang, Dapeng Hu, Jiashi Feng:
Do We Really Need to Access the Source Data? Source Hypothesis Transfer for Unsupervised Domain Adaptation. CoRR abs/2002.08546 (2020) - [i12]Jian Liang, Yunbo Wang, Dapeng Hu, Ran He, Jiashi Feng:
A Balanced and Uncertainty-aware Approach for Partial Domain Adaptation. CoRR abs/2003.02541 (2020) - [i11]Dapeng Hu, Jian Liang, Qibin Hou, Hanshu Yan, Yunpeng Chen, Shuicheng Yan, Jiashi Feng:
PANDA: Prototypical Unsupervised Domain Adaptation. CoRR abs/2003.13274 (2020) - [i10]Junqi Zhang, Bing Bai, Ye Lin, Jian Liang, Kun Bai, Fei Wang:
General-Purpose User Embeddings based on Mobile App Usage. CoRR abs/2005.13303 (2020) - [i9]Jian Liang, Bing Bai, Yuren Cao, Kun Bai, Fei Wang:
Adversarial Infidelity Learning for Model Interpretation. CoRR abs/2006.05379 (2020) - [i8]Bing Bai, Jian Liang, Guanhua Zhang, Hao Li, Kun Bai, Fei Wang:
Why is Attention Not So Attentive? CoRR abs/2006.05656 (2020) - [i7]Jian Liang, Dapeng Hu, Jiashi Feng:
Combating Domain Shift with Self-Taught Labeling. CoRR abs/2007.04171 (2020) - [i6]Jian Liang, Yuren Cao, Shuang Li, Bing Bai, Hao Li, Fei Wang, Kun Bai:
Domain Agnostic Learning for Unbiased Authentication. CoRR abs/2010.05250 (2020) - [i5]Shuang Li, Fangrui Lv, Binhui Xie, Chi Harold Liu, Jian Liang, Chen Qin:
Bi-Classifier Determinacy Maximization for Unsupervised Domain Adaptation. CoRR abs/2012.06995 (2020) - [i4]Jian Liang, Dapeng Hu, Yunbo Wang, Ran He, Jiashi Feng:
Source Data-absent Unsupervised Domain Adaptation through Hypothesis Transfer and Labeling Transfer. CoRR abs/2012.07297 (2020)
2010 – 2019
- 2019
- [j5]Jian Liang, Ran He, Zhenan Sun, Tieniu Tan:
Aggregating Randomized Clustering-Promoting Invariant Projections for Domain Adaptation. IEEE Trans. Pattern Anal. Mach. Intell. 41(5): 1027-1042 (2019) - [j4]Jian Liang, Ran He, Zhenan Sun, Tieniu Tan:
Exploring uncertainty in pseudo-label guided unsupervised domain adaptation. Pattern Recognit. 96 (2019) - [j3]Yunbo Wang, Jian Liang, Dong Cao, Zhenan Sun:
Local Semantic-Aware Deep Hashing With Hamming-Isometric Quantization. IEEE Trans. Image Process. 28(6): 2665-2679 (2019) - [c13]Jian Liang, Ran He, Zhenan Sun, Tieniu Tan:
Distant Supervised Centroid Shift: A Simple and Efficient Approach to Visual Domain Adaptation. CVPR 2019: 2975-2984 - 2018
- [c12]Weikuo Guo, Jian Liang, Xiangwei Kong, Lingxiao Song, Ran He:
X-GACMN: An X-Shaped Generative Adversarial Cross-Modal Network with Hypersphere Embedding. ACCV (5) 2018: 513-529 - [c11]Lingxiao He, Jian Liang, Haiqing Li, Zhenan Sun:
Deep Spatial Feature Reconstruction for Partial Person Re-Identification: Alignment-Free Approach. CVPR 2018: 7073-7082 - [c10]Jianze Wei, Jian Liang, Ran He, Jinfeng Yang:
Learning Discriminative Geodesic Flow Kernel for Unsupervised Domain Adaptation. ICME 2018: 1-6 - [i3]Lingxiao He, Jian Liang, Haiqing Li, Zhenan Sun:
Deep Spatial Feature Reconstruction for Partial Person Re-identification: Alignment-Free Approach. CoRR abs/1801.00881 (2018) - 2017
- [j2]Dekui Ma, Jian Liang, Ran He, Xiangwei Kong:
Nonlinear Discrete Cross-Modal Hashing for Visual-Textual Data. IEEE Multim. 24(2): 56-65 (2017) - [c9]Yanbo Fan, Ran He, Jian Liang, Bao-Gang Hu:
Self-Paced Learning: An Implicit Regularization Perspective. AAAI 2017: 1877-1883 - [c8]Xi Zhang, Jian Liang, Cao Xiao, Yize Zhao, Fei Wang:
Subtyping Parkinson's Disease with Recurrent Neural Network Models. AMIA 2017 - [c7]Chao Che, Cao Xiao, Jian Liang, Bo Jin, Jiayu Zho, Fei Wang:
An RNN Architecture with Dynamic Temporal Matching for Personalized Predictions of Parkinson's Disease. SDM 2017: 198-206 - [i2]Yanbo Fan, Jian Liang, Ran He, Bao-Gang Hu, Siwei Lyu:
Robust Localized Multi-view Subspace Clustering. CoRR abs/1705.07777 (2017) - 2016
- [c6]Jian Liang, Ran He, Zhenan Sun, Tieniu Tan:
Group-Invariant Cross-Modal Subspace Learning. IJCAI 2016: 1739-1745 - [c5]Dekui Ma, Jian Liang, Xiangwei Kong, Ran He, Ying Li:
Discrete Cross-Modal Hashing for Efficient Multimedia Retrieval. ISM 2016: 38-43 - [c4]Dekui Ma, Jian Liang, Xiangwei Kong, Ran He:
Frustratingly Easy Cross-Modal Hashing. ACM Multimedia 2016: 237-241 - [c3]Jian Liang, Zhihang Li, Dong Cao, Ran He, Jingdong Wang:
Self-Paced Cross-Modal Subspace Matching. SIGIR 2016: 569-578 - [i1]Yanbo Fan, Ran He, Jian Liang, Bao-Gang Hu:
Self-Paced Learning: an Implicit Regularization Perspective. CoRR abs/1606.00128 (2016) - 2015
- [j1]Shu Zhang, Jian Liang, Ran He, Zhenan Sun:
Code Consistent Hashing Based on Information-Theoretic Criterion. IEEE Trans. Big Data 1(3): 84-94 (2015) - [c2]Jian Liang, Dong Cao, Ran He, Zhenan Sun, Tieniu Tan:
Principal affinity based cross-modal retrieval. ACPR 2015: 126-130 - [c1]Lingxiao Song, Man Zhang, Zhenan Sun, Jian Liang, Ran He:
Two-Step Greedy Subspace Clustering. PCM (1) 2015: 45-54
Coauthor Index
[j14] [c46] [c45] [c44] [c43] [c42] [i56] [i55] [i54] [i53] [i52] [j13] [j12] [c41] [c39] [c36] [i45] [i44] [i42] [i41] [i39] [i38] [i37] [i36] [i35] [i33] [i32] [j10] [c30] [c26] [i28] [i26] [i24] [i22] [i15] [c17] [i12] [i4] [j5] [j4] [c13] [c12] [c10] [j2] [c9] [i2] [c6] [c5] [c4] [c3] [i1] [j1] [c2] [c1]
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