2023
- Revisiting AUC-oriented Adversarial Training with Loss-Agnostic Perturbations
Zhiyong Yang, Qianqian Xu, Wenzheng Hou, Shilong Bao, Yuan He, Xiaochun Cao and Qingming Huang. Revisiting AUC-oriented Adversarial Training with Loss-Agnostic Perturbations. IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 45(12): 15494–15511, Dec. 2023. [code] - AUC-Oriented Domain Adaptation: From Theory to Algorithm
Zhiyong Yang, Qianqian Xu, Shilong Bao, Peisong Wen, Yuan He, Xiaochun Cao and Qingming Huang. AUC-Oriented Domain Adaptation: From Theory to Algorithm. IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 45(12): 14161–14174, Dec. 2023. [code] - Positive-Unlabeled Learning with Label Distribution Alignment
Yangbangyan Jiang, Qianqian Xu, Yunrui Zhao, Zhiyong Yang, Peisong Wen, Xiaochun Cao, and Qingming Huang. Positive-Unlabeled Learning with Label Distribution Alignment. IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 45(12): 15345–15363, Dec. 2023. - Mitigating Confounding Bias in Practical Recommender Systems with Partially Inaccessible Exposure Status
Tianwei Cao, Qianqian Xu, Zhiyong Yang and Qingming Huang. Mitigating Confounding Bias in Practical Recommender Systems with Partially Inaccessible Exposure Status. IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2023. (Accepted) [code] - Feature Directions Matters: Long-Tailed Learning via Rotated Balanced Representation
Peifeng Gao, Qianqian Xu, Peisong Wen, Zhiyong Yang, Huiyang Shao and Qingming Huang. Feature Directions Matters: Long-Tailed Learning via Rotated Balanced Representation. International Conference on Machine Learning (ICML), 27542–27563, 2023. [code] - A Unified Generalization Analysis of Re-Weighting and Logit-Adjustment for Imbalanced Learning
Zitai Wang, Qianqian Xu, Zhiyong Yang, Yuan He, Xiaochun Cao and Qingming Huang. A Unified Generalization Analysis of Re-Weighting and Logit-Adjustment for Imbalanced Learning. Annual Conference on Neural Information Processing Systems (NeurIPS), 2023. (Accepted, Spotlight) [pdf] [code] - Weighted ROC Curve in Cost Space: Extending AUC to Cost-Sensitive Learning
Huiyang Shao, Qianqian Xu, Zhiyong Yang, Peisong Wen, Gao Peifeng, Qingming Huang. Weighted ROC Curve in Cost Space: Extending AUC to Cost-Sensitive Learning. Annual Conference on Neural Information Processing Systems (NeurIPS), 2023. (Accepted) [code] - DRAUC: An Instance-wise Distributionally Robust AUC Optimization Framework
Siran Dai, Qianqian Xu, Zhiyong Yang, Xiaochun Cao, Qingming Huang. DRAUC: An Instance-wise Distributionally Robust AUC Optimization Framework. Annual Conference on Neural Information Processing Systems (NeurIPS), 2023. (Accepted) [code] - Towards Decision-Friendly AUC: Learning Multi-Classifier with AUCµ
Peifeng Gao, Qianqian Xu, Peisong Wen, Huiyang Shao, Yuan He and Qingming Huang. Towards Decision-Friendly AUC: Learning Multi-Classifier with AUCµ. AAAI Conference on Artificial Intelligence (AAAI), 7633–7641, 2023. [pdf] [code] - Building Bridge Across the Time: Disruption and Restoration of Murals In the Wild
Huiyang Shao, Qianqian Xu, Peisong Wen, Gao Peifeng, Zhiyong Yang and Qingming Huang. Building Bridge Across the Time: Disruption and Restoration of Murals In the Wild. International Conference on Computer Vision (ICCV), 20259–20269, 2023. [code] - PSNEA: Pseudo-Siamese Network for Entity Alignment between Multi-modal Knowledge Graphs
Wenxin Ni, Qianqian Xu, Yangbangyan Jiang, Zongsheng Cao, Xiaochun Cao and Qingming Huang. PSNEA: Pseudo-Siamese Network for Entity Alignment between Multi-modal Knowledge Graphs. ACM Conference on Multimedia (ACM MM), 3489–3497, 2023. [code] - When Measures are Unreliable: Imperceptible Adversarial Perturbations toward Top-k Multi-Label Learning
Yuchen Sun, Qianqian Xu, Zitai Wang and Qingming Huang. When Measures are Unreliable: Imperceptible Adversarial Perturbations toward Top-k Multi-Label Learning. ACM Conference on Multimedia (ACM MM), 1515–1526, 2023. [pdf] [code]
2022
- Rethinking Label Flipping Attack: From Sample Masking to Sample Thresholding
Qianqian Xu, Zhiyong Yang, Yunrui Zhao, Xiaochun Cao and Qingming Huang. Rethinking Label Flipping Attack: From Sample Masking to Sample Thresholding. IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 45(6): 7668–7685, Jun. 2023. - Optimizing Two-way Partial AUC with an End-to-end Framework
Zhiyong Yang, Qianqian Xu, Shilong Bao, Yuan He, Xiaochun Cao and Qingming Huang. Optimizing Two-way Partial AUC with an End-to-end Framework. IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 45(8): 10228-10246, Aug. 2023. [pdf] [code] - A Tale of HodgeRank and Spectral Method: Target Attack Against Rank Aggregation is the Fixed Point of Adversarial Game
Ke Ma, Qianqian Xu, Jinshan Zeng, Guorong Li, Xiaochun Cao and Qingming Huang. A Tale of HodgeRank and Spectral Method: Target Attack Against Rank Aggregation is the Fixed Point of Adversarial Game. IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 45(4): 4090–4108, Apr. 2023. [pdf] [code] - Optimizing Partial Area Under the Top-k Curve: Theory and Practice
Zitai Wang, Qianqian Xu, Zhiyong Yang, Yuan He, Xiaochun Cao and Qingming Huang. Optimizing Partial Area Under the Top-k Curve: Theory and Practice. IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 45(4): 5053–5069, Apr. 2023. [pdf] [code] - MaxMatch: Semi-Supervised Learning with Worst-Case Consistency
Yangbangyan Jiang, Xiaodan Li, Yuefeng Chen, Yuan He, Qianqian Xu, Zhiyong Yang, Xiaochun Cao and Qingming Huang. MaxMatch: Semi-Supervised Learning with Worst-Case Consistency. IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 45(5): 5970–5987, May 2023. [pdf] [code] - AdAUC: End-to-end Adversarial AUC Optimization Against Long-tail Problems
Wenzheng Hou, Qianqian Xu, Zhiyong Yang, Shilong Bao, Yuan He and Qingming Huang. AdAUC: End-to-end Adversarial AUC Optimization Against Long-tail Problems. International Conference on Machine Learning (ICML), 8903–8925, 2022. [pdf] [code] - Exploring the Algorithm-Dependent Generalization of AUPRC Optimization with List Stability
Peisong Wen, Qianqian Xu, Zhiyong Yang, Yuan He and Qingming Huang. Exploring the Algorithm-Dependent Generalization of AUPRC Optimization with List Stability. Annual Conference on Neural Information Processing Systems (NeurIPS), 28335–28349, 2022. [pdf] [code] - OpenAUC: Towards AUC-Oriented Open-Set Recognition
Zitai Wang, Qianqian Xu, Zhiyong Yang, Yuan He, Xiaochun Cao and Qingming Huang. OpenAUC: Towards AUC-Oriented Open-Set Recognition. Annual Conference on Neural Information Processing Systems (NeurIPS), 25033–25045, 2022. (Spotlight) [pdf] [code] - The Minority Matters: A Diversity-Promoting Collaborative Metric Learning Algorithm
Shilong Bao, Qianqian Xu, Zhiyong Yang, Yuan He, Xiaochun Cao and Qingming Huang. The Minority Matters: A Diversity-Promoting Collaborative Metric Learning Algorithm. Annual Conference on Neural Information Processing Systems (NeurIPS), 2451–2464, 2022. (Oral) [pdf] [code] - OTKGE: Multi-modal Knowledge Graph Embeddings via Optimal Transport
Zongsheng Cao, Qianqian Xu, Zhiyong Yang, Yuan He, Xiaochun Cao and Qingming Huang. OTKGE: Multi-modal Knowledge Graph Embeddings via Optimal Transport. Annual Conference on Neural Information Processing Systems (NeurIPS), 39090–39102, 2022. - Asymptotically Unbiased Instance-wise Regularized Partial AUC Optimization: Theory and Algorithm
Huiyang Shao, Qianqian Xu, Zhiyong Yang, Shilong Bao and Qingming Huang. Asymptotically Unbiased Instance-wise Regularized Partial AUC Optimization: Theory and Algorithm. Annual Conference on Neural Information Processing Systems (NeurIPS), 38667–38679, 2022. [pdf] [code] - Dist-PU: Positive-Unlabeled Learning from a Label Distribution Perspective
Yunrui Zhao, Qianqian Xu, Yangbangyan Jiang, Peisong Wen and Qingming Huang. Dist-PU: Positive-Unlabeled Learning from a Label Distribution Perspective. IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 14461–14470, 2022. [pdf] [supp] [code] - Geometry Interaction Knowledge Graph Embeddings
Zongsheng Cao, Qianqian Xu, Zhiyong Yang, Xiaochun Cao and Qingming Huang. Geometry Interaction Knowledge Graph Embeddings. AAAI Conference on Artificial Intelligence (AAAI), 5521–5529, 2022. [pdf] [supp&code] - ER: Equivariance Regularizer for Knowledge Graph Completion
Zongsheng Cao, Qianqian Xu, Zhiyong Yang and Qingming Huang. ER: Equivariance Regularizer for Knowledge Graph Completion. AAAI Conference on Artificial Intelligence (AAAI), 5512–5520, 2022. [pdf] [supp&code] - Quaternion Ordinal Embedding
Wenzheng Hou, Qianqian Xu, Ke Ma, Qianxiu Hao, Qingming Huang. Quaternion Ordinal Embedding. International Joint Conference on Artificial Intelligence (IJCAI), 2066–2072, 2022. [pdf] [code] - Confederated Learning: Going Beyond Centralization
Zitai Wang, Qianqian Xu, Ke Ma, Xiaochun Cao and Qingming Huang. Confederated Learning: Going Beyond Centralization. ACM Conference on Multimedia (ACM MM), 2939–2947, 2022. (Oral) [pdf] [code] [slides] - Pay Attention to Your Positive Pairs: Positive Pair Aware Contrastive Knowledge Distillation
Zhipeng Yu, Qianqian Xu, Yangbangyan Jiang, Haoyu Qin and Qingming Huang. Pay Attention to Your Positive Pairs: Positive Pair Aware Contrastive Knowledge Distillation. ACM Conference on Multimedia (ACM MM), 5862–5870, 2022. (Oral) [pdf] [code] - Recurrent Meta-Learning against Generalized Cold-start problem in CTR Prediction
Junyu Chen, Qianqian Xu, Zhiyong Yang, Ke Ma, Xiaochun Cao and Qingming Huang. Recurrent Meta-Learning against Generalized Cold-start problem in CTR Prediction. ACM Conference on Multimedia (ACM MM), 2636–2644, 2022. [pdf] [code] - A Unified Framework against Topology and Class Imbalance
Junyu Chen, Qianqian Xu, Zhiyong Yang, Xiaochun Cao and Qingming Huang. A Unified Framework against Topology and Class Imbalance. ACM Conference on Multimedia (ACM MM), 180–188, 2022. [pdf] [code]
2021
- Not All Samples are Trustworthy: Towards Deep Robust SVP Prediction
Qianqian Xu, Zhiyong Yang, Yangbangyan Jiang, Xiaochun Cao, Yuan Yao and Qingming Huang. Not All Samples are Trustworthy: Towards Deep Robust SVP Prediction. IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 44(6): 3154–3169, Jun. 2022. (Regular paper) [pdf] [code] - Evaluating Visual Properties via Robust HodgeRank
Qianqian Xu, Jiechao Xiong, Xiaochun Cao, Qingming Huang and Yuan Yao. Evaluating Visual Properties via Robust HodgeRank. International Journal of Computer Vision (IJCV), 129(5): 1732–1753, Mar. 2021. (Regular paper) [pdf] - Poisoning Attack against Estimating from Pairwise Comparisons
Ke Ma, Qianqian Xu, Jinshan Zeng, Xiaochun Cao and Qingming Huang. Poisoning Attack against Estimating from Pairwise Comparisons. IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 44(10): 6393–6408, Oct. 2022. [pdf] [code] - Learning with Multiclass AUC: Theory and Algorithms
Zhiyong Yang, Qianqian Xu, Shilong Bao, Xiaochun Cao and Qingming Huang. Learning with Multiclass AUC: Theory and Algorithms. IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 44(11): 7747–7763, Nov. 2022. [pdf] [code] - Meta-Wrapper: Differentiable Wrapping Operator for User Interest Selection in CTR Prediction
Tianwei Cao, Qianqian Xu, Zhiyong Yang and Qingming Huang. Meta-Wrapper: Differentiable Wrapping Operator for User Interest Selection in CTR Prediction. IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 44(11): 8449–8464, Nov. 2022. [pdf] [code] - Rethinking Collaborative Metric Learning: Toward an Efficient Alternative without Negative Sampling
Shilong Bao, Qianqian Xu, Zhiyong Yang, Xiaochun Cao and Qingming Huang. Rethinking Collaborative Metric Learning: Toward an Efficient Alternative without Negative Sampling. IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 45(1): 1017–1035, Jan. 2023. [pdf] [code] - When All We Need is a Piece of the Pie: A Generic Framework for Optimizing Two-way Partial AUC
Zhiyong Yang, Qianqian Xu, Shilong Bao, Yuan He, Xiaochun Cao and Qingming Huang. When All We Need is a Piece of the Pie: A Generic Framework for Optimizing Two-way Partial AUC. International Conference on Machine Learning (ICML), 11820–11829, 2021. (Long talk) [pdf] [code] [slides] [poster] [video] - When False Positive is Intolerant: End-to-End Optimization with Low FPR for Multipartite Ranking
Peisong Wen, Qianqian Xu, Zhiyong Yang, Yuan He and Qingming Huang. When False Positive is Intolerant: End-to-End Optimization with Low FPR for Multipartite Ranking. Annual Conference on Neural Information Processing Systems (NeurIPS), 5025–-5037, 2021. (Poster) [pdf] [code] - Deep Partial Rank Aggregation for Personalized Attributes
Qianqian Xu, Zhiyong Yang, Zuyao Chen, Yangbangyan Jiang, Xiaochun Cao, Yuan Yao and Qingming Huang. Deep Partial Rank Aggregation for Personalized Attributes. AAAI Conference on Artificial Intelligence (AAAI), 678–688, 2021. [pdf] [code] - Seeking the Shape of Sound: An Adaptive Framework for Learning Voice-Face Association
Peisong Wen, Qianqian Xu, Yangbangyan Jiang, Zhiyong Yang, Yuan He and Qingming Huang. Seeking the Shape of Sound: An Adaptive Framework for Learning Voice-Face Association. IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 16347–16356, 2021. [pdf] [code] - Fast Stochastic Ordinal Embedding with Variance Reduction and Adaptive Step Size
Ke Ma, Jinshan Zeng, Jiechao Xiong, Qianqian Xu, Xiaochun Cao, Wei Liu and Yuan Yao. Fast Stochastic Ordinal Embedding with Variance Reduction and Adaptive Step Size. IEEE Transactions on Knowledge and Data Engineering (TKDE), 33(6): 2467–2478, Jun. 2021. [pdf] [code] - What to Select: Pursuing Consistent Motion Segmentation from Multiple Geometric Models
Yangbangyan Jiang, Qianqian Xu, Ke Ma, Zhiyong Yang, Xiaochun Cao and Qingming Huang. What to Select: Pursuing Consistent Motion Segmentation from Multiple Geometric Models. AAAI Conference on Artificial Intelligence (AAAI), 1708–1716, 2021. [pdf] [code] [supp] - Dual Quaternion Knowledge Graph Embeddings
Zongsheng Cao, Qianqian Xu, Zhiyong Yang, Xiaochun Cao and Qingming Huang. Dual Quaternion Knowledge Graph Embeddings. AAAI Conference on Artificial Intelligence (AAAI), 6894–6902, 2021. [pdf] [code] [supp] - Learning Meta-path-aware Embeddings for Recommender Systems
Qianxiu Hao, Qianqian Xu, Zhiyong Yang and Qingming Huang. Learning Meta-path-aware Embeddings for Recommender Systems. ACM Conference on Multimedia (ACM MM), 3909–3917, 2021. (Oral) [pdf] [code] - Pareto Optimality for Fairness-constrained Collaborative Filtering
Qianxiu Hao, Qianqian Xu, Zhiyong Yang and Qingming Huang. Pareto Optimality for Fairness-constrained Collaborative Filtering. ACM Conference on Multimedia (ACM MM), 5619–5627, 2021. [pdf] [code] - Implicit feedbacks are not always favorable: Iterative Relabeled One-Class Collaborative Filtering against Noisy Interactions
Zitai Wang, Qianqian Xu, Zhiyong Yang, Xiaochun Cao and Qingming Huang. Implicit feedbacks are not always favorable: Iterative Relabeled One-Class Collaborative Filtering against Noisy Interactions. ACM Conference on Multimedia (ACM MM), 3070–3078, 2021. [pdf] [code] [poster] [slides] - DPANet: Depth Potentiality-Aware Gated Attention Network for RGB-D Salient Object Detection
Zuyao Chen, Runmin Cong, Qianqian Xu and Qingming Huang. DPANet: Depth Potentiality-Aware Gated Attention Network for RGB-D Salient Object Detection. IEEE Transactions on Image Processing (TIP), 30: 7012–7024, Aug. 2021. [pdf] [code]
2020
- Who Likes What? – SplitLBI in Exploring Preferential Diversity of Ratings
Qianqian Xu, Jiechao Xiong, Zhiyong Yang, Xiaochun Cao, Qingming Huang and Yuan Yao. Who Likes What? – SplitLBI in Exploring Preferential Diversity of Ratings. AAAI Conference on Artificial Intelligence (AAAI), 262–269, 2020. (Oral) [pdf] [supp] [slides] - Task-Feature Collaborative Learning with Application to Personalized Attribute Prediction
Zhiyong Yang, Qianqian Xu, Xiaochun Cao and Qingming Huang. Task-Feature Collaborative Learning with Application to Personalized Attribute Prediction. IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 43(11): 4094–4110, Nov. 2021. (Regular paper) [pdf] [code] - Global Context-Aware Progressive Aggregation Network for Salient Object Detection
Zuyao Chen, Qianqian Xu, Ruimin Cong and Qingming Huang. Global Context-Aware Progressive Aggregation Network for Salient Object Detection. AAAI Conference on Artificial Intelligence (AAAI), 10599–10606, 2020. (Oral) [pdf] [code] - DMVOS: Discriminative Matching for Real-time Video Object Segmentation
Peisong Wen, Ruolin Yang, Qianqian Xu, Chen Qian, Qingming Huang, Runmin Cong, Jianlou Si. DMVOS: Discriminative Matching for Real-time Video Object Segmentation. ACM Conference on Multimedia (ACM MM), 2048–2056, 2020. - Quaternion-Based Knowledge Graph Network for Recommendation
Zhaopeng Li, Qianqian Xu, Yangbangyan Jiang, Xiaochun Cao and Qingming Huang. Quaternion-Based Knowledge Graph Network for Recommendation. ACM Conference on Multimedia (ACM MM), 880–888, 2020. [code] - Task-distribution-aware Meta-learning for Cold-start CTR Prediction
Tianwei Cao, Qianqian Xu, Zhiyong Yang and Qingming Huang. Task-distribution-aware Meta-learning for Cold-start CTR Prediction. ACM Conference on Multimedia (ACM MM), 3514–3522, 2020. [pdf] [code] - IR-GAN: Image Manipulation with Linguistic Instruction by Increment Reasoning
Zhenhuan Liu, Jincan Deng, Liang Li, Shaofei Cai, Qianqian Xu, Shuhui Wang and Qingming Huang. IR-GAN: Image Manipulation with Linguistic Instruction by Increment Reasoning. ACM Conference on Multimedia (ACM MM), 322–330, 2020. [pdf] - NuI-Go: Recursive Non-local Encoder-Decoder Network for Retinal Image Non-uniform Illumination Removal
Chongyi Li, Huazhu Fu, Runmin Cong, Zechao Li and Qianqian Xu. NuI-Go: Recursive Non-local Encoder-Decoder Network for Retinal Image Non-uniform Illumination Removal. ACM Conference on Multimedia (ACM MM), 1478–1487, 2020. [pdf] - Neural Collaborative Preference Learning with Pairwise Comparisons
Zhaopeng Li, Qianqian Xu, Yangbangyan Jiang, Ke Ma, Xiaochun Cao and Qingming Huang. Neural Collaborative Preference Learning with Pairwise Comparisons. IEEE Transactions on Multimedia (TMM), 23: 1977-1989, Dec. 2021. [pdf] [code] - RGB-D Salient Object Detection with Cross Modality Modulation and Selection
Chongyi Li, Runmin Cong, Yongri Piao, Qianqian Xu and Chen Change Loy. RGB-D Salient Object Detection with Cross Modality Modulation and Selection. European Conference on Computer Vision (ECCV), 225–241, 2020. [pdf]
2019
- From Social to Individuals: a Parsimonious Path of Multi-level Models for Crowdsourced Preference Aggregation
Qianqian Xu, Jiechao Xiong, Xiaochun Cao, Qingming Huang and Yuan Yao. From Social to Individuals: a Parsimonious Path of Multi-level Models for Crowdsourced Preference Aggregation. IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 41(4): 844–856, Apr. 2019. (Regular paper) [pdf] [code] - iSplit LBI: Individualized Partial Ranking with Ties via Split LBI
Qianqian Xu, Xinwei Sun, Zhiyong Yang, Xiaochun Cao, Qingming Huang and Yuan Yao. iSplit LBI: Individualized Partial Ranking with Ties via Split LBI. Annual Conference on Neural Information Processing Systems (NeurIPS), 3896–3906, 2019. (Poster) [pdf] [code] [poster] - Deep Robust Subjective Visual Property Prediction in Crowdsourcing
Qianqian Xu, Zhiyong Yang, Yangbangyan Jiang, Xiaochun Cao, Qingming Huang and Yuan Yao. Deep Robust Subjective Visual Property Prediction in Crowdsourcing. IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 8993–9001, 2019. (Poster) [pdf] [code] [poster] - Generalized Block-Diagonal Structure Pursuit: Learning Soft Latent Task Assignment against Negative Transfer
Zhiyong Yang, Qianqian Xu, Yangbangyan Jiang, Xiaochun Cao and Qingming Huang. Generalized Block-Diagonal Structure Pursuit: Learning Soft Latent Task Assignment against Negative Transfer. Annual Conference on Neural Information Processing Systems (NeurIPS), 5846–5857, 2019. (Poster) [pdf] [code] [poster] - DM2C: Deep Mixed-Modal Clustering
Yangbangyan Jiang, Qianqian Xu, Zhiyong Yang, Xiaochun Cao and Qingming Huang. DM2C: Deep Mixed-Modal Clustering. Annual Conference on Neural Information Processing Systems (NeurIPS), 5880–5890, 2019. (Spotlight) [pdf] [code] [poster] [slides] - Learning Personalized Attribute Preference via Multi-task AUC Optimization
Zhiyong Yang, Qianqian Xu, Xiaochun Cao and Qingming Huang. Learning Personalized Attribute Preference via Multi-task AUC Optimization. AAAI Conference on Artificial Intelligence (AAAI), 5660–5667, 2019. (Oral) [pdf] [code] [poster] [slides] - Less but Better: Generalization Enhancement of Ordinal Embedding via Distributional Margin
Ke Ma, Qianqian Xu, Zhiyong Yang and Xiaochun Cao. Less but Better: Generalization Enhancement of Ordinal Embedding via Distributional Margin. AAAI Conference on Artificial Intelligence (AAAI), 2978–2985, 2019. (Poster) [pdf] [code] [poster] - Robust Ordinal Embedding from Contaminated Relative Comparisons
Ke Ma, Qianqian Xu and Xiaochun Cao. Robust Ordinal Embedding from Contaminated Relative Comparisons. AAAI Conference on Artificial Intelligence (AAAI), 7908–7915, 2019. (Poster) [pdf] [code] [poster] - Split Multiplicative Multi-view Subspace Clustering
Zhiyong Yang, Qianqian Xu, Weigang Zhang, Xiaochun Cao and Qingming Huang. Split Multiplicative Multi-view Subspace Clustering. IEEE Transactions on Image Processing (TIP), 28(10): 5147–5160, May 2019. (Regular paper) [pdf] [code] - Collaborative Preference Embedding against Sparse Labels
Shilong Bao, Qianqian Xu, Ke Ma, Zhiyong Yang, Xiaochun Cao and Qingming Huang. Collaborative Preference Embedding against Sparse Labels. ACM Conference on Multimedia (ACM MM), 2079–2087, 2019. (Oral) [pdf] [code] [poster] [slides] - Adversarial Preference Learning with Pairwise Comparisons
Zitai Wang, Qianqian Xu, Ke Ma, Yangbangyan Jiang, Xiaochun Cao and Qingming Huang. Adversarial Preference Learning with Pairwise Comparisons. ACM Conference on Multimedia (ACM MM), 656–664, 2019. (Oral) [pdf] [code] [poster] [slides] - Duet Robust Deep Subspace Clustering
Yangbangyan Jiang, Qianqian Xu, Zhiyong Yang, Xiaochun Cao and Qingming Huang. Duet Robust Deep Subspace Clustering. ACM Conference on Multimedia (ACM MM), 1596–1604, 2019. (Spotlight) [pdf] [code] [poster] [slides] - Low-Light Image Enhancement via a Deep Hybrid Network
Wenqi Ren, Sifei Liu, Lin Ma, Qianqian Xu, Xiangyu Xu, Xiaochun Cao, Junping Du and Ming-Hsuan Yang. Low-Light Image Enhancement via a Deep Hybrid Network. IEEE Transactions on Image Processing (TIP), 28(9): 4364–4375, Sep. 2019. (Regular paper) [pdf] [code]
2018
- A Margin-based MLE for Crowdsourced Partial Ranking
Qianqian Xu, Jiechao Xiong, Xinwei Sun, Zhiyong Yang, Xiaochun Cao, Qingming Huang and Yuan Yao. A Margin-based MLE for Crowdsourced Partial Ranking. ACM Conference on Multimedia (ACM MM), 591–599, 2018. (Full paper) [pdf] [code] [poster] - HodgeRank with Information Maximization for Crowdsourced Pairwise Ranking Aggregation
Qianqian Xu, Jiechao Xiong, Xi Chen, Qingming Huang and Yuan Yao. HodgeRank with Information Maximization for Crowdsourced Pairwise Ranking Aggregation. AAAI Conference on Artificial Intelligence (AAAI), 4326–4334, 2018. (Oral) [pdf] [code] [dataset] - From Common to Special: When Multi-Attribute Learning Meets Personalized Opinions
Zhiyong Yang, Qianqian Xu, Xiaochun Cao and Qingming Huang. From Common to Special: When Multi-Attribute Learning Meets Personalized Opinions. AAAI Conference on Artificial Intelligence (AAAI), 515–522, 2018. (Poster) [pdf] [code] [poster] - Stochastic Non-convex Ordinal Embedding with Stabilized Barzilai-Borwein Step Size
Ke Ma, Jinshan Zeng, Jiechao Xiong, Qianqian Xu, Xiaochun Cao, Wei Liu and Yuan Yao. Stochastic Non-convex Ordinal Embedding with Stabilized Barzilai-Borwein Step Size. AAAI Conference on Artificial Intelligence (AAAI), 3738–3745, 2018. (Poster) [pdf] [code] [poster] - When to Learn What: Deep Cognitive Subspace Clustering
Yangbangyan Jiang, Zhiyong Yang, Qianqian Xu, Xiaochun Cao and Qingming Huang. When to Learn What: Deep Cognitive Subspace Clustering. ACM Conference on Multimedia (ACM MM), 718–726, 2018. (Full paper) [pdf] [code] [poster]
2017
- Exploring Outliers in Crowdsourced Ranking for QoE
Qianqian Xu, Ming Yan, Chendi Huang, Jiechao Xiong, Qingming Huang, and Yuan Yao. Exploring Outliers in Crowdsourced Ranking for QoE. ACM Conference on Multimedia (ACM MM), 1540–1548, 2017. (Oral) [pdf] [code]
2016
- False Discovery Rate Control and Statistical Quality Assessment of Annotators in Crowdsourced Ranking
Qianqian Xu, Jiechao Xiong, Xiaochun Cao, and Yuan Yao. False Discovery Rate Control and Statistical Quality Assessment of Annotators in Crowdsourced Ranking. International Conference on Machine Learning (ICML), 1282–1291, 2016. (Oral) [pdf] [code] - Parsimonious Mixed-Effects HodgeRank for Crowdsourced Preference Aggregation
Qianqian Xu, Jiechao Xiong, Xiaochun Cao, and Yuan Yao. Parsimonious Mixed-Effects HodgeRank for Crowdsourced Preference Aggregation. ACM Conference on Multimedia (ACM MM), 841–850, 2016. (Full paper) [pdf] [code] - Analysis of crowdsourced sampling strategies for HodgeRank with sparse random graphs
Braxton Osting, Jiechao Xiong, Qianqian Xu, and Yuan Yao. Analysis of crowdsourced sampling strategies for HodgeRank with sparse random graphs. Applied and Computational Harmonic Analysis (ACHA), 41(2): 540–560, 2016. [pdf] [code]
2014
- Online HodgeRank on Random Graphs for Crowdsourceable QoE Evaluation
Qianqian Xu, Jiechao Xiong, Qingming Huang, and Yuan Yao. Online HodgeRank on Random Graphs for Crowdsourceable QoE Evaluation. IEEE Transactions on Multimedia (TMM), 16(2): 373–386, Feb. 2014. (Regular paper) [pdf] [code] [dataset]
2013
- Robust Evaluation for Quality of Experience in Crowdsourcing
Qianqian Xu, Jiechao Xiong, Qingming Huang, and Yuan Yao. Robust Evaluation for Quality of Experience in Crowdsourcing. ACM Conference on Multimedia (ACM MM), 43–52, 2013. (Full paper) [pdf] [code] [PC-IQA dataset] [PC-VQA dataset]
2012
- Online Crowdsourcing Subjective Image Quality Assessment
Qianqian Xu, Qingming Huang and Yuan Yao. Online Crowdsourcing Subjective Image Quality Assessment. ACM Conference on Multimedia (ACM MM), 359–368, 2012. (Full paper) [pdf] [code] [dataset] - HodgeRank on Random Graphs for Subjective Video Quality Assessment
Qianqian Xu, Qingming Huang, Tingting Jiang, Bowei Yan, Weisi Lin and Yuan Yao. HodgeRank on Random Graphs for Subjective Video Quality Assessment. IEEE Transactions on Multimedia (TMM), 14(3): 844–857, Jun. 2012. (Regular paper) [pdf] [code] [dataset]
2011
- Random Partial Paired Comparison for Subjective Video Quality Assessment via HodgeRank
Qianqian Xu, Tingting Jiang, Yuan Yao, Qingming Huang, Bowei Yan and Weisi Lin. Random Partial Paired Comparison for Subjective Video Quality Assessment via HodgeRank. ACM Conference on Multimedia (ACM MM), 393–402, 2011. (Full paper) [pdf] [code] [dataset]