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2020 – today
- 2024
[j25]Xiuyuan Hu, Guoqing Liu, Quanming Yao, Yang Zhao, Hao Zhang:
Hamiltonian diversity: effectively measuring molecular diversity by shortest Hamiltonian circuits. J. Cheminformatics 16(1): 94 (2024)- [j24]Quanming Yao
, Zhenqian Shen, Yaqing Wang, Dejing Dou:
Property-Aware Relation Networks for Few-Shot Molecular Property Prediction. IEEE Trans. Pattern Anal. Mach. Intell. 46(8): 5413-5429 (2024) - [j23]Lanning Wei, Huan Zhao, Zhiqiang He, Quanming Yao:
Neural Architecture Search for GNN-Based Graph Classification. ACM Trans. Inf. Syst. 42(1): 1:1-1:29 (2024) - [c74]Lebin Yu, Yunbo Qiu, Quanming Yao, Yuan Shen, Xudong Zhang, Jian Wang:
Robust Communicative Multi-Agent Reinforcement Learning with Active Defense. AAAI 2024: 17575-17582 - [c73]Quanming Yao:
Towards Human-like Learning from Relational Structured Data. AAAI 2024: 22684 - [c72]Guangyi Liu, Quanming Yao, Yongqi Zhang, Lei Chen:
Knowledge-Enhanced Recommendation with User-Centric Subgraph Network. ICDE 2024: 1269-1281 - [c71]Haiquan Qiu, Yongqi Zhang, Yong Li, Quanming Yao:
Understanding Expressivity of GNN in Rule Learning. ICLR 2024 - [c70]Zhanke Zhou, Yongqi Zhang, Jiangchao Yao, Quanming Yao, Bo Han:
Less is More: One-shot Subgraph Reasoning on Large-scale Knowledge Graphs. ICLR 2024 - [c69]Shiguang Wu, Yaqing Wang, Quanming Yao:
PACIA: Parameter-Efficient Adapter for Few-Shot Molecular Property Prediction. IJCAI 2024: 5208-5216 - [c68]Yaqing Wang, Hongming Piao, Daxiang Dong, Quanming Yao, Jingbo Zhou:
Warming Up Cold-Start CTR Prediction by Learning Item-Specific Feature Interactions. KDD 2024: 3233-3244 - [c67]Juzheng Zhang, Lanning Wei, Zhen Xu, Quanming Yao:
Heuristic Learning with Graph Neural Networks: A Unified Framework for Link Prediction. KDD 2024: 4223-4231 - [i87]Lanning Wei, Jun Gao, Huan Zhao, Quanming Yao:
Towards Versatile Graph Learning Approach: from the Perspective of Large Language Models. CoRR abs/2402.11641 (2024) - [i86]Zhen Hao Wong, Hansi Yang, Xiaoyi Fu, Quanming Yao:
Loss-aware Curriculum Learning for Heterogeneous Graph Neural Networks. CoRR abs/2402.18875 (2024) - [i85]Zhanke Zhou, Yongqi Zhang, Jiangchao Yao, Quanming Yao, Bo Han:
Less is More: One-shot Subgraph Reasoning on Large-scale Knowledge Graphs. CoRR abs/2403.10231 (2024) - [i84]Haiquan Qiu, Yatao Bian, Quanming Yao:
Graph Unitary Message Passing. CoRR abs/2403.11199 (2024) - [i83]Guangyi Liu, Quanming Yao, Yongqi Zhang, Lei Chen:
Knowledge-Enhanced Recommendation with User-Centric Subgraph Network. CoRR abs/2403.14377 (2024) - [i82]Guangyi Liu, Yongqi Zhang, Yong Li, Quanming Yao:
Explore then Determine: A GNN-LLM Synergy Framework for Reasoning over Knowledge Graph. CoRR abs/2406.01145 (2024) - [i81]Juzheng Zhang, Lanning Wei, Zhen Xu, Quanming Yao:
Heuristic Learning with Graph Neural Networks: A Unified Framework for Link Prediction. CoRR abs/2406.07979 (2024) - [i80]Yongqiang Chen, Quanming Yao, Juzheng Zhang, James Cheng, Yatao Bian:
HIGHT: Hierarchical Graph Tokenization for Graph-Language Alignment. CoRR abs/2406.14021 (2024) - [i79]Quanming Yao, Yongqi Zhang, Yaqing Wang, Nan Yin, James Kwok, Qiang Yang:
Knowledge-Aware Parsimony Learning: A Perspective from Relational Graphs. CoRR abs/2407.00478 (2024) - [i78]Yaqing Wang, Hongming Piao, Daxiang Dong, Quanming Yao, Jingbo Zhou:
Warming Up Cold-Start CTR Prediction by Learning Item-Specific Feature Interactions. CoRR abs/2407.10112 (2024) - [i77]Juzheng Zhang, Yatao Bian, Yongqiang Chen, Quanming Yao:
UniMoT: Unified Molecule-Text Language Model with Discrete Token Representation. CoRR abs/2408.00863 (2024) - 2023
- [j22]Yongqi Zhang, Quanming Yao, Ling Yue, Xian Wu, Ziheng Zhang, Zhenxi Lin, Yefeng Zheng:
Emerging drug interaction prediction enabled by a flow-based graph neural network with biomedical network. Nat. Comput. Sci. 3(12): 1023-1033 (2023) - [j21]Yongqi Zhang, Quanming Yao, James T. Kwok:
Bilinear Scoring Function Search for Knowledge Graph Learning. IEEE Trans. Pattern Anal. Mach. Intell. 45(2): 1458-1473 (2023) - [j20]Hui Zhang, Quanming Yao, James T. Kwok, Xiang Bai:
Searching a High Performance Feature Extractor for Text Recognition Network. IEEE Trans. Pattern Anal. Mach. Intell. 45(5): 6231-6246 (2023) - [j19]Huiming Chen, Huandong Wang, Quanming Yao, Yong Li, Depeng Jin, Qiang Yang:
LoSAC: An Efficient Local Stochastic Average Control Method for Federated Optimization. ACM Trans. Knowl. Discov. Data 17(4): 58:1-58:28 (2023) - [j18]Yunbo Tang, Dan Chen, Yiping Zuo, Xiaoqiang Lu, Rajiv Ranjan, Albert Y. Zomaya, Quanming Yao, Xiaoli Li:
Enhanced Bayesian Factorization With Variant Scale Partitioning for Multivariate Time Series Analysis. IEEE Trans. Knowl. Data Eng. 35(4): 3832-3845 (2023) - [j17]Zhen Xu, Quanming Yao, Yong Li, Qiang Yang:
Understanding and Simplifying Architecture Search in Spatio-Temporal Graph Neural Networks. Trans. Mach. Learn. Res. 2023 (2023) - [c66]Lebin Yu, Yunbo Qiu, Quanming Yao, Xudong Zhang, Jian Wang:
Improving Zero-Shot Coordination Performance Based on Policy Similarity. ICAPS 2023: 438-442 - [c65]Hansi Yang, Yongqi Zhang, Quanming Yao, James T. Kwok:
Positive-Unlabeled Node Classification with Structure-aware Graph Learning. CIKM 2023: 4390-4394 - [c64]Ling Yue, Yongqi Zhang, Quanming Yao, Yong Li, Xian Wu, Ziheng Zhang, Zhenxi Lin, Yefeng Zheng:
Relation-aware Ensemble Learning for Knowledge Graph Embedding. EMNLP 2023: 16620-16631 - [c63]Yongqi Zhang, Hui Zhang, Quanming Yao, Jun Wan:
Combining Self-Supervised and Supervised Learning with Noisy Labels. ICIP 2023: 605-609 - [c62]Hongzhi Shi, Jingtao Ding, Yufan Cao, Quanming Yao, Li Liu, Yong Li:
Learning Symbolic Models for Graph-structured Physical Mechanism. ICLR 2023 - [c61]Jianing Zhu, Jiangchao Yao, Tongliang Liu, Quanming Yao, Jianliang Xu, Bo Han:
Combating Exacerbated Heterogeneity for Robust Models in Federated Learning. ICLR 2023 - [c60]Zhanke Zhou, Chenyu Zhou, Xuan Li, Jiangchao Yao, Quanming Yao, Bo Han:
On Strengthening and Defending Graph Reconstruction Attack with Markov Chain Approximation. ICML 2023: 42843-42877 - [c59]Xu Wang, Huan Zhao, Wei-Wei Tu, Quanming Yao:
Automated 3D Pre-Training for Molecular Property Prediction. KDD 2023: 2419-2430 - [c58]Yongqi Zhang, Zhanke Zhou, Quanming Yao, Xiaowen Chu, Bo Han:
AdaProp: Learning Adaptive Propagation for Graph Neural Network based Knowledge Graph Reasoning. KDD 2023: 3446-3457 - [c57]Zhenqian Shen, Hansi Yang, Yong Li, James T. Kwok, Quanming Yao:
Efficient Hyper-parameter Optimization with Cubic Regularization. NeurIPS 2023 - [c56]Zhanke Zhou, Jiangchao Yao, Jiaxu Liu, Xiawei Guo, Quanming Yao, LI He, Liang Wang, Bo Zheng, Bo Han:
Combating Bilateral Edge Noise for Robust Link Prediction. NeurIPS 2023 - [c55]Lanning Wei, Zhiqiang He, Huan Zhao, Quanming Yao:
Search to Capture Long-range Dependency with Stacking GNNs for Graph Classification. WWW 2023: 588-598 - [c54]Shiguang Wu, Yaqing Wang, Qinghe Jing, Daxiang Dong, Dejing Dou, Quanming Yao:
ColdNAS: Search to Modulate for User Cold-Start Recommendation. WWW 2023: 1021-1031 - [c53]Hongzhi Shi, Quanming Yao, Yong Li:
Learning to Simulate Crowd Trajectories with Graph Networks. WWW 2023: 4200-4209 - [i76]Lebin Yu, Yunbo Qiu, Quanming Yao, Xudong Zhang, Jian Wang:
Improving Zero-Shot Coordination Performance Based on Policy Similarity. CoRR abs/2302.05063 (2023) - [i75]Lanning Wei, Zhiqiang He, Huan Zhao, Quanming Yao:
Search to Capture Long-range Dependency with Stacking GNNs for Graph Classification. CoRR abs/2302.08671 (2023) - [i74]Jianing Zhu, Jiangchao Yao, Tongliang Liu, Quanming Yao, Jianliang Xu, Bo Han:
Combating Exacerbated Heterogeneity for Robust Models in Federated Learning. CoRR abs/2303.00250 (2023) - [i73]Haiquan Qiu, Yongqi Zhang, Yong Li, Quanming Yao:
Logical Expressiveness of Graph Neural Network for Knowledge Graph Reasoning. CoRR abs/2303.12306 (2023) - [i72]Shiguang Wu, Yaqing Wang, Qinghe Jing, Daxiang Dong, Dejing Dou, Quanming Yao:
ColdNAS: Search to Modulate for User Cold-Start Recommendation. CoRR abs/2306.03387 (2023) - [i71]Xu Wang, Huan Zhao, Weiwei Tu, Quanming Yao:
Automated 3D Pre-Training for Molecular Property Prediction. CoRR abs/2306.07812 (2023) - [i70]Zhanke Zhou, Chenyu Zhou, Xuan Li, Jiangchao Yao, Quanming Yao, Bo Han:
On Strengthening and Defending Graph Reconstruction Attack with Markov Chain Approximation. CoRR abs/2306.09104 (2023) - [i69]Lanning Wei, Zhiqiang He, Huan Zhao, Quanming Yao:
Unleashing the Power of Graph Learning through LLM-based Autonomous Agents. CoRR abs/2309.04565 (2023) - [i68]Shiguang Wu, Yaqing Wang, Quanming Yao:
Hierarchical Adaptation with Hypernetworks for Few-shot Molecular Property Prediction. CoRR abs/2310.00614 (2023) - [i67]Ling Yue, Yongqi Zhang, Quanming Yao, Yong Li, Xian Wu, Ziheng Zhang, Zhenxi Lin, Yefeng Zheng:
Relation-aware Ensemble Learning for Knowledge Graph Embedding. CoRR abs/2310.08917 (2023) - [i66]Hansi Yang, Yongqi Zhang, Quanming Yao, James T. Kwok:
Positive-Unlabeled Node Classification with Structure-aware Graph Learning. CoRR abs/2310.13538 (2023) - [i65]Zhen Hao Wong, Ling Yue, Quanming Yao:
Ensemble Learning for Graph Neural Networks. CoRR abs/2310.14166 (2023) - [i64]Zhanke Zhou, Jiangchao Yao, Jiaxu Liu, Xiawei Guo, Quanming Yao, Li He, Liang Wang, Bo Zheng, Bo Han:
Combating Bilateral Edge Noise for Robust Link Prediction. CoRR abs/2311.01196 (2023) - [i63]Yongqi Zhang, Quanming Yao, Ling Yue, Xian Wu, Ziheng Zhang, Zhenxi Lin, Yefeng Zheng:
Emerging Drug Interaction Prediction Enabled by Flow-based Graph Neural Network with Biomedical Network. CoRR abs/2311.09261 (2023) - [i62]Yaqing Wang, Zaifei Yang, Quanming Yao:
Accurate and interpretable drug-drug interaction prediction enabled by knowledge subgraph learning. CoRR abs/2311.15056 (2023) - [i61]Lebin Yu, Yunbo Qiu, Quanming Yao, Yuan Shen, Xudong Zhang, Jian Wang:
Robust Communicative Multi-Agent Reinforcement Learning with Active Defense. CoRR abs/2312.11545 (2023) - 2022
- [j16]Zhen Xu, Lanning Wei, Huan Zhao, Rex Ying, Quanming Yao, Wei-Wei Tu, Isabelle Guyon:
Bridging the Gap of AutoGraph Between Academia and Industry: Analyzing AutoGraph Challenge at KDD Cup 2020. Frontiers Artif. Intell. 5 (2022) - [j15]Quanming Yao, Yaqing Wang, Bo Han, James T. Kwok:
Low-rank Tensor Learning with Nonconvex Overlapped Nuclear Norm Regularization. J. Mach. Learn. Res. 23: 136:1-136:60 (2022) - [j14]Wei He, Quanming Yao, Chao Li, Naoto Yokoya, Qibin Zhao, Hongyan Zhang, Liangpei Zhang:
Non-Local Meets Global: An Iterative Paradigm for Hyperspectral Image Restoration. IEEE Trans. Pattern Anal. Mach. Intell. 44(4): 2089-2107 (2022) - [j13]Quanming Yao, Hansi Yang, En-Liang Hu, James T. Kwok:
Efficient Low-Rank Semidefinite Programming With Robust Loss Functions. IEEE Trans. Pattern Anal. Mach. Intell. 44(10): 6153-6168 (2022) - [j12]Zhen Xu, Sergio Escalera, Adrien Pavão, Magali Richard, Wei-Wei Tu, Quanming Yao, Huan Zhao, Isabelle Guyon:
Codabench: Flexible, easy-to-use, and reproducible meta-benchmark platform. Patterns 3(7): 100543 (2022) - [c52]Yongqi Zhang, Zhanke Zhou, Quanming Yao, Yong Li:
Efficient Hyper-parameter Search for Knowledge Graph Embedding. ACL (1) 2022: 2715-2735 - [c51]Wei He, Quanming Yao, Naoto Yokoya, Tatsumi Uezato, Hongyan Zhang, Liangpei Zhang:
Spectrum-Aware and Transferable Architecture Search for Hyperspectral Image Restoration. ECCV (19) 2022: 19-37 - [c50]Zhen Wang, Haotong Du, Quanming Yao, Xuelong Li:
Search to Pass Messages for Temporal Knowledge Graph Completion. EMNLP (Findings) 2022: 6160-6172 - [c49]Kaixin Zheng, Yaqing Wang, Quanming Yao, Dejing Dou:
Simplified Graph Learning for Inductive Short Text Classification. EMNLP 2022: 10717-10724 - [c48]Haiquan Qiu, Yao Wang, Shaojie Tang, Deyu Meng, Quanming Yao:
Fast and Provable Nonconvex Tensor RPCA. ICML 2022: 18211-18249 - [c47]Yongqi Zhang, Quanming Yao:
Knowledge Graph Reasoning with Relational Digraph. WWW 2022: 912-924 - [i60]Zhen Xu, Lanning Wei, Huan Zhao, Rex Ying, Quanming Yao, Wei-Wei Tu, Isabelle Guyon:
Bridging the Gap of AutoGraph between Academia and Industry: Analysing AutoGraph Challenge at KDD Cup 2020. CoRR abs/2204.02625 (2022) - [i59]Yongqi Zhang, Zhanke Zhou, Quanming Yao, Yong Li:
KGTuner: Efficient Hyper-parameter Search for Knowledge Graph Learning. CoRR abs/2205.02460 (2022) - [i58]Quanming Yao, Yaqing Wang, Bo Han, James T. Kwok:
Low-rank Tensor Learning with Nonconvex Overlapped Nuclear Norm Regularization. CoRR abs/2205.03059 (2022) - [i57]Yongqi Zhang, Zhanke Zhou, Quanming Yao, Xiaowen Chu, Bo Han:
Learning Adaptive Propagation for Knowledge Graph Reasoning. CoRR abs/2205.15319 (2022) - [i56]Xu Wang, Huan Zhao, Lanning Wei, Quanming Yao:
Graph Property Prediction on Open Graph Benchmark: A Winning Solution by Graph Neural Architecture Search. CoRR abs/2207.06027 (2022) - [i55]Hansi Yang, Yongqi Zhang, Quanming Yao:
AutoWeird: Weird Translational Scoring Function Identified by Random Search. CoRR abs/2207.11673 (2022) - [i54]Yinfeng Li, Chen Gao, Quanming Yao, Tong Li, Depeng Jin, Yong Li:
DisenHCN: Disentangled Hypergraph Convolutional Networks for Spatiotemporal Activity Prediction. CoRR abs/2208.06794 (2022) - [i53]Hui Zhang, Quanming Yao, James T. Kwok, Xiang Bai:
Searching a High-Performance Feature Extractor for Text Recognition Network. CoRR abs/2209.13139 (2022) - [i52]Zhen Wang, Haotong Du, Quanming Yao, Xuelong Li:
Search to Pass Messages for Temporal Knowledge Graph Completion. CoRR abs/2210.16740 (2022) - [i51]Lanning Wei, Zhiqiang He, Huan Zhao, Quanming Yao:
Enhancing Intra-class Information Extraction for Heterophilous Graphs: One Neural Architecture Search Approach. CoRR abs/2211.10990 (2022) - 2021
- [j11]Yaqing Wang, Quanming Yao, James T. Kwok, Lionel M. Ni:
Generalizing from a Few Examples: A Survey on Few-shot Learning. ACM Comput. Surv. 53(3): 63:1-63:34 (2021) - [j10]Wei Zheng, Zhen Wang, Quanming Yao, Xuelong Li:
WRTRe: Weighted relative position transformer for joint entity and relation extraction. Neurocomputing 459: 315-326 (2021) - [j9]Hugo Jair Escalante, Quanming Yao, Wei-Wei Tu, Nelishia Pillay, Rong Qu, Yang Yu, Neil Houlsby:
Guest Editorial: Automated Machine Learning. IEEE Trans. Pattern Anal. Mach. Intell. 43(9): 2887-2890 (2021) - [j8]Huan Zhao, Quanming Yao, Yangqiu Song, James T. Kwok, Dik Lun Lee:
Side Information Fusion for Recommender Systems over Heterogeneous Information Network. ACM Trans. Knowl. Discov. Data 15(4): 60:1-60:32 (2021) - [j7]Yongqi Zhang, Quanming Yao, Lei Chen:
Simple and automated negative sampling for knowledge graph embedding. VLDB J. 30(2): 259-285 (2021) - [c46]Lanning Wei, Huan Zhao, Quanming Yao, Zhiqiang He:
Pooling Architecture Search for Graph Classification. CIKM 2021: 2091-2100 - [c45]Yaqing Wang, Song Wang, Quanming Yao, Dejing Dou:
Hierarchical Heterogeneous Graph Representation Learning for Short Text Classification. EMNLP (1) 2021: 3091-3101 - [c44]Huan Zhao, Quanming Yao, Weiwei Tu:
Search to aggregate neighborhood for graph neural network. ICDE 2021: 552-563 - [c43]Shimin Di, Quanming Yao, Yongqi Zhang, Lei Chen:
Efficient Relation-aware Scoring Function Search for Knowledge Graph Embedding. ICDE 2021: 1104-1115 - [c42]Yuhui Ding, Quanming Yao, Huan Zhao, Tong Zhang:
DiffMG: Differentiable Meta Graph Search for Heterogeneous Graph Neural Networks. KDD 2021: 279-288 - [c41]Chen Gao, Quanming Yao, Depeng Jin, Yong Li:
Efficient Data-specific Model Search for Collaborative Filtering. KDD 2021: 415-425 - [c40]Chen Gao, Yinfeng Li, Quanming Yao, Depeng Jin, Yong Li:
Progressive Feature Interaction Search for Deep Sparse Network. NeurIPS 2021: 392-403 - [c39]Fengli Xu, Quanming Yao, Pan Hui, Yong Li:
Automorphic Equivalence-aware Graph Neural Network. NeurIPS 2021: 15138-15150 - [c38]Yaqing Wang, Abulikemu Abuduweili, Quanming Yao, Dejing Dou:
Property-Aware Relation Networks for Few-Shot Molecular Property Prediction. NeurIPS 2021: 17441-17454 - [c37]Yaqing Wang, Quanming Yao, James T. Kwok:
A Scalable, Adaptive and Sound Nonconvex Regularizer for Low-rank Matrix Learning. WWW 2021: 1798-1808 - [c36]Yu Liu, Quanming Yao, Yong Li:
Role-Aware Modeling for N-ary Relational Knowledge Bases. WWW 2021: 2660-2671 - [c35]Shimin Di, Quanming Yao, Lei Chen:
Searching to Sparsify Tensor Decomposition for N-ary Relational Data. WWW 2021: 4043-4054 - [i50]Hansi Yang, Quanming Yao, James T. Kwok:
Tensorizing Subgraph Search in the Supernet. CoRR abs/2101.01078 (2021) - [i49]Huan Zhao, Quanming Yao, Wei-Wei Tu:
Search to aggregate neighborhood for graph neural network. CoRR abs/2104.06608 (2021) - [i48]Yu Liu, Quanming Yao, Yong Li:
Role-Aware Modeling for N-ary Relational Knowledge Bases. CoRR abs/2104.09780 (2021) - [i47]Shimin Di, Quanming Yao, Lei Chen:
Searching to Sparsify Tensor Decomposition for N-ary Relational Data. CoRR abs/2104.10625 (2021) - [i46]Shimin Di, Quanming Yao, Yongqi Zhang, Lei Chen:
Efficient Relation-aware Scoring Function Search for Knowledge Graph Embedding. CoRR abs/2104.10880 (2021) - [i45]Chen Gao, Quanming Yao, Depeng Jin, Yong Li:
Efficient Data-specific Model Search for Collaborative Filtering. CoRR abs/2106.07453 (2021) - [i44]Yongqi Zhang, Zhanke Zhou, Quanming Yao:
AutoSF+: Towards Automatic Scoring Function Design for Knowledge Graph Embedding. CoRR abs/2107.00184 (2021) - [i43]Yongqi Zhang, Quanming Yao:
Knowledge Graph Reasoning with Relational Directed Graph. CoRR abs/2108.06040 (2021) - [i42]Xiawei Guo, Yuhan Quan, Huan Zhao, Quanming Yao, Yong Li, Weiwei Tu:
TabGNN: Multiplex Graph Neural Network for Tabular Data Prediction. CoRR abs/2108.09127 (2021) - [i41]Lanning Wei, Huan Zhao, Quanming Yao, Zhiqiang He:
Pooling Architecture Search for Graph Classification. CoRR abs/2108.10587 (2021) - [i40]Yaqing Wang, Song Wang, Quanming Yao, Dejing Dou:
Hierarchical Heterogeneous Graph Representation Learning for Short Text Classification. CoRR abs/2111.00180 (2021) - [i39]Huiming Chen, Huandong Wang, Quanming Yao, Yong Li, Depeng Jin, Qiang Yang:
LoSAC: An Efficient Local Stochastic Average Control Method for Federated Optimization. CoRR abs/2112.07839 (2021) - 2020
- [c34]Quanming Yao, Ju Xu, Wei-Wei Tu, Zhanxing Zhu:
Efficient Neural Architecture Search via Proximal Iterations. AAAI 2020: 6664-6671 - [c33]Huan Zhao, Lanning Wei, Quanming Yao:
Simplifying Architecture Search for Graph Neural Network. CIKM (Workshops) 2020 - [c32]Hui Zhang, Quanming Yao, Mingkun Yang, Yongchao Xu, Xiang Bai:
AutoSTR: Efficient Backbone Search for Scene Text Recognition. ECCV (24) 2020: 751-767 - [c31]Yongqi Zhang, Quanming Yao, Wenyuan Dai, Lei Chen:
AutoSF: Searching Scoring Functions for Knowledge Graph Embedding. ICDE 2020: 433-444 - [c30]Hongzhi Shi, Quanming Yao, Qi Guo, Yaguang Li, Lingyu Zhang, Jieping Ye, Yong Li, Yan Liu:
Predicting Origin-Destination Flow via Multi-Perspective Graph Convolutional Network. ICDE 2020: 1818-1821 - [c29]Bo Han, Gang Niu, Xingrui Yu, Quanming Yao, Miao Xu, Ivor W. Tsang, Masashi Sugiyama:
SIGUA: Forgetting May Make Learning with Noisy Labels More Robust. ICML 2020: 4006-4016 - [c28]Quanming Yao, Hansi Yang, Bo Han, Gang Niu, James Tin-Yau Kwok:
Searching to Exploit Memorization Effect in Learning with Noisy Labels. ICML 2020: 10789-10798 - [c27]Rishabh Mehrotra, Ben Carterette, Yong Li, Quanming Yao, Chen Gao, James T. Kwok, Qiang Yang, Isabelle Guyon:
Advances in Recommender Systems: From Multi-stakeholder Marketplaces to Automated RecSys. KDD 2020: 3533-3534 - [c26]Jingtao Ding, Yuhan Quan, Quanming Yao, Yong Li, Depeng Jin:
Simplify and Robustify Negative Sampling for Implicit Collaborative Filtering. NeurIPS 2020 - [c25]Yongqi Zhang, Quanming Yao, Lei Chen:
Interstellar: Searching Recurrent Architecture for Knowledge Graph Embedding. NeurIPS 2020 - [c24]Yu Liu, Quanming Yao, Yong Li:
Generalizing Tensor Decomposition for N-ary Relational Knowledge Bases. WWW 2020: 1104-1114 - [c23]Quanming Yao, Xiangning Chen, James T. Kwok, Yong Li, Cho-Jui Hsieh:
Efficient Neural Interaction Function Search for Collaborative Filtering. WWW 2020: 1660-1670 - [p1]Xiawei Guo, Quanming Yao, James T. Kwok, Wei-Wei Tu, Yuqiang Chen, Wenyuan Dai, Qiang Yang:
Privacy-Preserving Stacking with Application to Cross-organizational Diabetes Prediction. Federated Learning 2020: 269-283 - [i38]Hui Zhang, Quanming Yao, Mingkun Yang, Yongchao Xu, Xiang Bai:
Efficient Backbone Search for Scene Text Recognition. CoRR abs/2003.06567 (2020) - [i37]Yu Liu, Quanming Yao, Yong Li:
Generalizing Tensor Decomposition for N-ary Relational Knowledge Bases. CoRR abs/2007.03988 (2020) - [i36]Yaqing Wang, Quanming Yao, James T. Kwok:
Efficient Low-Rank Matrix Learning by Factorizable Nonconvex Regularization. CoRR abs/2008.06542 (2020) - [i35]Huan Zhao, Lanning Wei, Quanming Yao:
Simplifying Architecture Search for Graph Neural Network. CoRR abs/2008.11652 (2020) - [i34]Jingtao Ding, Yuhan Quan, Quanming Yao, Yong Li, Depeng Jin:
Simplify and Robustify Negative Sampling for Implicit Collaborative Filtering. CoRR abs/2009.03376 (2020) - [i33]Yuhui Ding, Quanming Yao, Tong Zhang:
Propagation Model Search for Graph Neural Networks. CoRR abs/2010.03250 (2020) - [i32]Wei He, Quanming Yao, Chao Li, Naoto Yokoya, Qibin Zhao, Hongyan Zhang, Liangpei Zhang:
Non-local Meets Global: An Iterative Paradigm for Hyperspectral Image Restoration. CoRR abs/2010.12921 (2020) - [i31]Yongqi Zhang, Quanming Yao, Lei Chen:
Efficient, Simple and Automated Negative Sampling for Knowledge Graph Embedding. CoRR abs/2010.14227 (2020) - [i30]Fengli Xu, Quanming Yao, Pan Hui, Yong Li:
Graph Neural Network with Automorphic Equivalence Filters. CoRR abs/2011.04218 (2020) - [i29]Bo Han, Quanming Yao, Tongliang Liu, Gang Niu, Ivor W. Tsang, James T. Kwok, Masashi Sugiyama:
A Survey of Label-noise Representation Learning: Past, Present and Future. CoRR abs/2011.04406 (2020) - [i28]Hui Zhang, Quanming Yao:
Decoupling Representation and Classifier for Noisy Label Learning. CoRR abs/2011.08145 (2020)
2010 – 2019
- 2019
- [j6]Bo Han, Quanming Yao, Yuangang Pan, Ivor W. Tsang, Xiaokui Xiao, Qiang Yang, Masashi Sugiyama:
Millionaire: a hint-guided approach for crowdsourcing. Mach. Learn. 108(5): 831-858 (2019) - [j5]Quanming Yao, James T. Kwok, Taifeng Wang, Tie-Yan Liu:
Large-Scale Low-Rank Matrix Learning with Nonconvex Regularizers. IEEE Trans. Pattern Anal. Mach. Intell. 41(11): 2628-2643 (2019) - [j4]Quanming Yao, James T. Kwok:
Accelerated and Inexact Soft-Impute for Large-Scale Matrix and Tensor Completion. IEEE Trans. Knowl. Data Eng. 31(9): 1665-1679 (2019) - [c22]Wei He, Quanming Yao, Chao Li, Naoto Yokoya, Qibin Zhao:
Non-Local Meets Global: An Integrated Paradigm for Hyperspectral Denoising. CVPR 2019: 6868-6877 - [c21]Yongqi Zhang, Quanming Yao, Yingxia Shao, Lei Chen:
NSCaching: Simple and Efficient Negative Sampling for Knowledge Graph Embedding. ICDE 2019: 614-625 - [c20]Quanming Yao, James Tin-Yau Kwok, Bo Han:
Efficient Nonconvex Regularized Tensor Completion with Structure-aware Proximal Iterations. ICML 2019: 7035-7044 - [c19]En-Liang Hu, Quanming Yao:
Robust Learning from Noisy Side-information by Semidefinite Programming. IJCAI 2019: 2514-2520 - [c18]Quanming Yao, Xiawei Guo, James T. Kwok, Wei-Wei Tu, Yuqiang Chen, Wenyuan Dai, Qiang Yang:
Privacy-Preserving Stacking with Application to Cross-organizational Diabetes Prediction. IJCAI 2019: 4114-4120 - [c17]Hongzhi Shi, Chao Zhang, Quanming Yao, Yong Li, Funing Sun, Depeng Jin:
State-Sharing Sparse Hidden Markov Models for Personalized Sequences. KDD 2019: 1549-1559 - [c16]Yuanfei Luo, Mengshuo Wang, Hao Zhou, Quanming Yao, Wei-Wei Tu, Yuqiang Chen, Wenyuan Dai, Qiang Yang:
AutoCross: Automatic Feature Crossing for Tabular Data in Real-World Applications. KDD 2019: 1936-1945 - [i27]Yaqing Wang, Quanming Yao:
Few-shot Learning: A Survey. CoRR abs/1904.05046 (2019) - [i26]Yongqi Zhang, Quanming Yao, Wenyuan Dai, Lei Chen:
AutoKGE: Searching Scoring Functions for Knowledge Graph Embedding. CoRR abs/1904.11682 (2019) - [i25]Yuanfei Luo, Mengshuo Wang, Hao Zhou, Quanming Yao, Wei-Wei Tu, Yuqiang Chen, Qiang Yang, Wenyuan Dai:
AutoCross: Automatic Feature Crossing for Tabular Data in Real-World Applications. CoRR abs/1904.12857 (2019) - [i24]En-Liang Hu, Quanming Yao:
Robust Learning from Noisy Side-information by Semidefinite Programming. CoRR abs/1905.04629 (2019) - [i23]Quanming Yao, Ju Xu, Wei-Wei Tu, Zhanxing Zhu:
Differentiable Neural Architecture Search via Proximal Iterations. CoRR abs/1905.13577 (2019) - [i22]Quanming Yao, Xiangning Chen, James T. Kwok, Yong Li:
Searching for Interaction Functions in Collaborative Filtering. CoRR abs/1906.12091 (2019) - [i21]Hansi Yang, Quanming Yao, Bo Han, Gang Niu:
Searching to Exploit Memorization Effect in Learning from Corrupted Labels. CoRR abs/1911.02377 (2019) - [i20]Yongqi Zhang, Quanming Yao, Lei Chen:
Neural Recurrent Structure Search for Knowledge Graph Embedding. CoRR abs/1911.07132 (2019) - 2018
- [j3]Yaqing Wang, Quanming Yao, James T. Kwok, Lionel M. Ni:
Scalable Online Convolutional Sparse Coding. IEEE Trans. Image Process. 27(10): 4850-4859 (2018) - [c15]Yaqing Wang, Quanming Yao, James Tin-Yau Kwok, Lionel M. Ni:
Online Convolutional Sparse Coding with Sample-Dependent Dictionary. ICML 2018: 5196-5205 - [c14]Quanming Yao, James T. Kwok:
Scalable Robust Matrix Factorization with Nonconvex Loss. NeurIPS 2018: 5066-5075 - [c13]Bo Han, Quanming Yao, Xingrui Yu, Gang Niu, Miao Xu, Weihua Hu, Ivor W. Tsang, Masashi Sugiyama:
Co-teaching: Robust training of deep neural networks with extremely noisy labels. NeurIPS 2018: 8536-8546 - [i19]Huan Zhao, Quanming Yao, Yangqiu Song, James T. Kwok, Dik Lun Lee:
Learning with Heterogeneous Side Information Fusion for Recommender Systems. CoRR abs/1801.02411 (2018) - [i18]Bo Han, Quanming Yao, Yuangang Pan, Ivor W. Tsang, Xiaokui Xiao, Qiang Yang, Masashi Sugiyama:
Millionaire: A Hint-guided Approach for Crowdsourcing. CoRR abs/1802.09172 (2018) - [i17]Bo Han, Quanming Yao, Xingrui Yu, Gang Niu, Miao Xu, Weihua Hu, Ivor W. Tsang, Masashi Sugiyama:
Co-sampling: Training Robust Networks for Extremely Noisy Supervision. CoRR abs/1804.06872 (2018) - [i16]Yaqing Wang, Quanming Yao, James T. Kwok, Lionel M. Ni:
Online Convolutional Sparse Coding with Sample-Dependent Dictionary. CoRR abs/1804.10366 (2018) - [i15]Quanming Yao:
Scalable Tensor Completion with Nonconvex Regularization. CoRR abs/1807.08725 (2018) - [i14]Quanming Yao, Mengshuo Wang, Hugo Jair Escalante, Isabelle Guyon, Yi-Qi Hu, Yu-Feng Li, Wei-Wei Tu, Qiang Yang, Yang Yu:
Taking Human out of Learning Applications: A Survey on Automated Machine Learning. CoRR abs/1810.13306 (2018) - [i13]Xiawei Guo, Quanming Yao, Wei-Wei Tu, Yuqiang Chen, Wenyuan Dai, Qiang Yang:
Privacy-preserving Transfer Learning for Knowledge Sharing. CoRR abs/1811.09491 (2018) - [i12]Wei He, Quanming Yao, Chao Li, Naoto Yokoya, Qibin Zhao:
Non-local Meets Global: An Integrated Paradigm for Hyperspectral Denoising. CoRR abs/1812.04243 (2018) - [i11]Yongqi Zhang, Quanming Yao, Yingxia Shao, Lei Chen:
NSCaching: Simple and Efficient Negative Sampling for Knowledge Graph Embedding. CoRR abs/1812.06410 (2018) - 2017
- [j2]Quanming Yao, James T. Kwok:
Efficient Learning with a Family of Nonconvex Regularizers by Redistributing Nonconvexity. J. Mach. Learn. Res. 18: 179:1-179:52 (2017) - [j1]Yi Yang, Quanming Yao, Huamin Qu:
VISTopic: A visual analytics system for making sense of large document collections using hierarchical topic modeling. Vis. Informatics 1(1): 40-47 (2017) - [c12]Xiawei Guo, Quanming Yao, James Tin-Yau Kwok:
Efficient Sparse Low-Rank Tensor Completion Using the Frank-Wolfe Algorithm. AAAI 2017: 1948-1954 - [c11]Huan Zhao, Quanming Yao, James T. Kwok, Dik Lun Lee:
Collaborative Filtering with Social Local Models. ICDM 2017: 645-654 - [c10]Lu Hou, Quanming Yao, James T. Kwok:
Loss-aware Binarization of Deep Networks. ICLR (Poster) 2017 - [c9]Quanming Yao, James T. Kwok, Fei Gao, Wei Chen, Tie-Yan Liu:
Efficient Inexact Proximal Gradient Algorithm for Nonconvex Problems. IJCAI 2017: 3308-3314 - [c8]Yaqing Wang, James T. Kwok, Quanming Yao, Lionel M. Ni:
Zero-shot learning with a partial set of observed attributes. IJCNN 2017: 3777-3784 - [c7]Huan Zhao, Quanming Yao, Jianda Li, Yangqiu Song, Dik Lun Lee:
Meta-Graph Based Recommendation Fusion over Heterogeneous Information Networks. KDD 2017: 635-644 - [i10]Quanming Yao, James T. Kwok:
Accelerated and Inexact Soft-Impute for Large-Scale Matrix and Tensor Completion. CoRR abs/1703.05487 (2017) - [i9]Huan Zhao, Quanming Yao, Dik Lun Lee:
Social Recommendation With Local Low Rank Matrix Approximation. CoRR abs/1704.05735 (2017) - [i8]Yaqing Wang, Quanming Yao, James T. Kwok, Lionel M. Ni:
Online Convolutional Sparse Coding. CoRR abs/1706.06972 (2017) - [i7]Quanming Yao, James T. Kwok, Taifeng Wang, Tie-Yan Liu:
Large-Scale Low-Rank Matrix Learning with Nonconvex Regularizers. CoRR abs/1708.00146 (2017) - [i6]Quanming Yao:
Efficient Robust Matrix Factorization with Nonconvex Penalties. CoRR abs/1710.07205 (2017) - 2016
- [c6]Quanming Yao, James T. Kwok:
Efficient Learning with a Family of Nonconvex Regularizers by Redistributing Nonconvexity. ICML 2016: 2645-2654 - [c5]Quanming Yao, James T. Kwok:
Greedy Learning of Generalized Low-Rank Models. IJCAI 2016: 2294-2300 - [i5]Quanming Yao, James T. Kwok:
Efficient Learning with a Family of Nonconvex Regularizers by Redistributing Nonconvexity. CoRR abs/1606.03841 (2016) - [i4]Quanming Yao, James T. Kwok:
Learning of Generalized Low-Rank Models: A Greedy Approach. CoRR abs/1607.08012 (2016) - [i3]Quanming Yao, James T. Kwok:
Fast Learning with Nonconvex L1-2 Regularization. CoRR abs/1610.09461 (2016) - [i2]Lu Hou, Quanming Yao, James T. Kwok:
Loss-aware Binarization of Deep Networks. CoRR abs/1611.01600 (2016) - 2015
- [c4]Quanming Yao, James T. Kwok:
Colorization by Patch-Based Local Low-Rank Matrix Completion. AAAI 2015: 1959-1965 - [c3]Quanming Yao, James T. Kwok, Wenliang Zhong:
Fast Low-Rank Matrix Learning with Nonconvex Regularization. ICDM 2015: 539-548 - [c2]Quanming Yao, James T. Kwok:
Accelerated Inexact Soft-Impute for Fast Large-Scale Matrix Completion. IJCAI 2015: 4002-4008 - [i1]Quanming Yao, James Tin-Yau Kwok, Wenliang Zhong:
Fast Low-Rank Matrix Learning with Nonconvex Regularization. CoRR abs/1512.00984 (2015) - 2012
- [c1]Quanming Yao, Xiubao Jiang, Mingming Gong, Xinge You, Yu Liu, Duanquan Xu:
Efficient Group Learning with Hypergraph Partition in Multi-task Learning. CCPR 2012: 9-16
Coauthor Index
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