Yiming Ying

ORCID

Publication Activity (10 Years)

Years Active: 2004-2024
Publications (10 Years): 80

Top Venues

Publications

Puyu Wang, Yunwen Lei, Yiming Ying, Ding-Xuan Zhou
Differentially private stochastic gradient descent with low-noise. Neurocomputing 585 (2024)
Zhenhuan Yang, Yingqiang Ge, Congzhe Su, Dingxian Wang, Xiaoting Zhao, Yiming Ying
Fairness-aware Differentially Private Collaborative Filtering. CoRR (2023)
Puyu Wang, Yunwen Lei, Di Wang, Yiming Ying, Ding-Xuan Zhou
Generalization Guarantees of Gradient Descent for Multi-Layer Neural Networks. CoRR (2023)
Bokun Wang, Zhuoning Yuan, Yiming Ying, Tianbao Yang
Memory-Based Optimization Methods for Model-Agnostic Meta-Learning and Personalized Federated Learning. J. Mach. Learn. Res. 24 (2023)
Ruogu Wang, Alex A. Lemus, Colin M. Henneberry, Yiming Ying, Yunlong Feng, Alex M. Valm
Unmixing biological fluorescence image data with sparse and low-rank Poisson regression. Bioinform. 39 (4) (2023)
Yunwen Lei, Tianbao Yang, Yiming Ying, Ding-Xuan Zhou
Generalization Analysis for Contrastive Representation Learning. CoRR (2023)
Lisha Chen, Heshan Fernando, Yiming Ying, Tianyi Chen
Three-Way Trade-Off in Multi-Objective Learning: Optimization, Generalization and Conflict-Avoidance. CoRR (2023)
Ming Yang, Xiyuan Wei, Tianbao Yang, Yiming Ying
Stability and Generalization of Stochastic Compositional Gradient Descent Algorithms. CoRR (2023)
Yunwen Lei, Tianbao Yang, Yiming Ying, Ding-Xuan Zhou
Generalization Analysis for Contrastive Representation Learning. ICML (2023)
Hanpu Shen, Cheng-Long Wang, Zihang Xiang, Yiming Ying, Di Wang
Differentially Private Non-convex Learning for Multi-layer Neural Networks. CoRR (2023)
Lisha Chen, Heshan Devaka Fernando, Yiming Ying, Tianyi Chen
Three-Way Trade-Off in Multi-Objective Learning: Optimization, Generalization and Conflict-Avoidance. NeurIPS (2023)
Zhenhuan Yang, Yingqiang Ge, Congzhe Su, Dingxian Wang, Xiaoting Zhao, Yiming Ying
Fairness-aware Differentially Private Collaborative Filtering. WWW (Companion Volume) (2023)
Shu Hu, Zhenhuan Yang, Xin Wang, Yiming Ying, Siwei Lyu
Outlier Robust Adversarial Training. CoRR (2023)
Zhenhuan Yang, Yan Lok Ko, Kush R. Varshney, Yiming Ying
Minimax AUC Fairness: Efficient Algorithm with Provable Convergence. AAAI (2023)
Dixian Zhu, Yiming Ying, Tianbao Yang
Label Distributionally Robust Losses for Multi-class Classification: Consistency, Robustness and Adaptivity. ICML (2023)
Tianbao Yang, Yiming Ying
AUC Maximization in the Era of Big Data and AI: A Survey. ACM Comput. Surv. 55 (8) (2023)
Shu Hu, Zhenhuan Yang, Xin Wang, Yiming Ying, Siwei Lyu
Outlier Robust Adversarial Training. ACML (2023)
Chengqiang Huang, Geyong Min, Yulei Wu, Yiming Ying, Ke Pei, Zuochang Xiang
Time Series Anomaly Detection for Trustworthy Services in Cloud Computing Systems. IEEE Trans. Big Data 8 (1) (2022)
Tianbao Yang, Yiming Ying
AUC Maximization in the Era of Big Data and AI: A Survey. CoRR (2022)
Shu Hu, Yiming Ying, Xin Wang, Siwei Lyu
Sum of Ranked Range Loss for Supervised Learning. J. Mach. Learn. Res. 23 (2022)
Siwei Lyu, Yanbo Fan, Yiming Ying, Bao-Gang Hu
Average Top-k Aggregate Loss for Supervised Learning. IEEE Trans. Pattern Anal. Mach. Intell. 44 (1) (2022)
Puyu Wang, Yunwen Lei, Yiming Ying, Ding-Xuan Zhou
Stability and Generalization for Markov Chain Stochastic Gradient Methods. NeurIPS (2022)
Heyuan Li, Yipeng Liu, Yiming Ying, Minfan Fu
Circular Capacitive Coupler for Stable Output Under Horizontal Misalignment. ISIE (2022)
Zhenhuan Yang, Shu Hu, Yunwen Lei, Kush R. Varshney, Siwei Lyu, Yiming Ying
Differentially Private SGDA for Minimax Problems. CoRR (2022)
Yunwen Lei, Rong Jin, Yiming Ying
Stability and Generalization Analysis of Gradient Methods for Shallow Neural Networks. CoRR (2022)
Zhenhuan Yang, Shu Hu, Yunwen Lei, Kush R. Varshney, Siwei Lyu, Yiming Ying
Differentially private SGDA for minimax problems. UAI (2022)
Puyu Wang, Yunwen Lei, Yiming Ying, Ding-Xuan Zhou
Stability and Generalization for Markov Chain Stochastic Gradient Methods. CoRR (2022)
Puyu Wang, Yunwen Lei, Yiming Ying, Ding-Xuan Zhou
Differentially Private Stochastic Gradient Descent with Low-Noise. CoRR (2022)
Zhenhuan Yang, Yan Lok Ko, Kush R. Varshney, Yiming Ying
Minimax AUC Fairness: Efficient Algorithm with Provable Convergence. CoRR (2022)
Yunwen Lei, Rong Jin, Yiming Ying
Stability and Generalization Analysis of Gradient Methods for Shallow Neural Networks. NeurIPS (2022)
Puyu Wang, Yunwen Lei, Yiming Ying, Hai Zhang
Differentially Private SGD with Non-Smooth Loss. CoRR (2021)
Yunwen Lei, Mingrui Liu, Yiming Ying
Generalization Guarantee of SGD for Pairwise Learning. NeurIPS (2021)
Zhuoning Yuan, Zhishuai Guo, Yi Xu, Yiming Ying, Tianbao Yang
Federated Deep AUC Maximization for Hetergeneous Data with a Constant Communication Complexity. ICML (2021)
Hitesh Sapkota, Yiming Ying, Feng Chen, Qi Yu
Distributionally Robust Optimization for Deep Kernel Multiple Instance Learning. AISTATS (2021)
Zhenhuan Yang, Yunwen Lei, Puyu Wang, Tianbao Yang, Yiming Ying
Simple Stochastic and Online Gradient Descent Algorithms for Pairwise Learning. CoRR (2021)
Zhuoning Yuan, Zhishuai Guo, Yi Xu, Yiming Ying, Tianbao Yang
Federated Deep AUC Maximization for Heterogeneous Data with a Constant Communication Complexity. CoRR (2021)
Yunwen Lei, Yiming Ying
Stochastic Proximal AUC Maximization. J. Mach. Learn. Res. 22 (2021)
Shu Hu, Yiming Ying, Xin Wang, Siwei Lyu
Sum of Ranked Range Loss for Supervised Learning. CoRR (2021)
Yunwen Lei, Yiming Ying
Sharper Generalization Bounds for Learning with Gradient-dominated Objective Functions. ICLR (2021)
Yunwen Lei, Zhenhuan Yang, Tianbao Yang, Yiming Ying
Stability and Generalization of Stochastic Gradient Methods for Minimax Problems. CoRR (2021)
Yunwen Lei, Zhenhuan Yang, Tianbao Yang, Yiming Ying
Stability and Generalization of Stochastic Gradient Methods for Minimax Problems. ICML (2021)
Zhenhuan Yang, Yunwen Lei, Puyu Wang, Tianbao Yang, Yiming Ying
Simple Stochastic and Online Gradient Descent Algorithms for Pairwise Learning. NeurIPS (2021)
Zhenhuan Yang, Yunwen Lei, Siwei Lyu, Yiming Ying
Stability and Differential Privacy of Stochastic Gradient Descent for Pairwise Learning with Non-Smooth Loss. AISTATS (2021)
Bokun Wang, Zhuoning Yuan, Yiming Ying, Tianbao Yang
Memory-based Optimization Methods for Model-Agnostic Meta-Learning. CoRR (2021)
Puyu Wang, Zhenhuan Yang, Yunwen Lei, Yiming Ying, Hai Zhang
Differentially private empirical risk minimization for AUC maximization. Neurocomputing 461 (2021)
Mingrui Liu, Zhuoning Yuan, Yiming Ying, Tianbao Yang
Stochastic AUC Maximization with Deep Neural Networks. ICLR (2020)
Zhenhuan Yang, Baojian Zhou, Yunwen Lei, Yiming Ying
Stochastic Hard Thresholding Algorithms for AUC Maximization. CoRR (2020)
Baojian Zhou, Yiming Ying, Steven Skiena
Online AUC Optimization for Sparse High-Dimensional Datasets. CoRR (2020)
Shu Hu, Yiming Ying, Xin Wang, Siwei Lyu
Learning by Minimizing the Sum of Ranked Range. CoRR (2020)
Yunwen Lei, Yiming Ying
Fine-Grained Analysis of Stability and Generalization for Stochastic Gradient Descent. ICML (2020)
Yunwen Lei, Yiming Ying
Fine-Grained Analysis of Stability and Generalization for Stochastic Gradient Descent. CoRR (2020)
Zhenhuan Yang, Baojian Zhou, Yunwen Lei, Yiming Ying
Stochastic Hard Thresholding Algorithms for AUC Maximization. ICDM (2020)
Baojian Zhou, Yiming Ying, Steven Skiena
Online AUC Optimization for Sparse High-Dimensional Datasets. ICDM (2020)
Shu Hu, Yiming Ying, Xin Wang, Siwei Lyu
Learning by Minimizing the Sum of Ranked Range. NeurIPS (2020)
Zhenhuan Yang, Yiming Ying, Qilong Min
Online optimization for residential PV-ESS energy system scheduling. Math. Found. Comput. 2 (1) (2019)
Michael Natole, Yiming Ying, Siwei Lyu
Stochastic AUC Optimization Algorithms With Linear Convergence. Frontiers Appl. Math. Stat. 5 (2019)
Baojian Zhou, Feng Chen, Yiming Ying
Dual Averaging Method for Online Graph-structured Sparsity. CoRR (2019)
Yunwen Lei, Yiming Ying
Stochastic Proximal AUC Maximization. CoRR (2019)
Mingrui Liu, Zhuoning Yuan, Yiming Ying, Tianbao Yang
Stochastic AUC Maximization with Deep Neural Networks. CoRR (2019)
Baojian Zhou, Feng Chen, Yiming Ying
Stochastic Iterative Hard Thresholding for Graph-structured Sparsity Optimization. CoRR (2019)
Wei Shen, Zhenhuan Yang, Yiming Ying, Xiaoming Yuan
Stability and Optimization Error of Stochastic Gradient Descent for Pairwise Learning. CoRR (2019)
Baojian Zhou, Feng Chen, Yiming Ying
Dual Averaging Method for Online Graph-structured Sparsity. KDD (2019)
Baojian Zhou, Feng Chen, Yiming Ying
Stochastic Iterative Hard Thresholding for Graph-structured Sparsity Optimization. ICML (2019)
Yunlong Feng, Yiming Ying
Learning with Correntropy-induced Losses for Regression with Mixture of Symmetric Stable Noise. CoRR (2018)
Julien Bohné, Yiming Ying, Stéphane Gentric, Massimiliano Pontil
Learning local metrics from pairwise similarity data. Pattern Recognit. 75 (2018)
Siwei Lyu, Yiming Ying
A Univariate Bound of Area Under ROC. UAI (2018)
Zhikui Chen, Fangming Zhong, Geyong Min, Yonglin Leng, Yiming Ying
Supervised Intra- and Inter-Modality Similarity Preserving Hashing for Cross-Modal Retrieval. IEEE Access 6 (2018)
Yi Wei, Ming-Ching Chang, Yiming Ying, Ser-Nam Lim, Siwei Lyu
Explain Black-box Image Classifications Using Superpixel-based Interpretation. ICPR (2018)
Chengqiang Huang, Yulei Wu, Geyong Min, Yiming Ying
Kernelized Convex Hull Approximation and its Applications in Data Description Tasks. IJCNN (2018)
Michael Natole, Yiming Ying, Siwei Lyu
Stochastic Proximal Algorithms for AUC Maximization. ICML (2018)
Yanbo Fan, Siwei Lyu, Yiming Ying, Bao-Gang Hu
Learning with Average Top-k Loss. CoRR (2017)
Zheng-Chu Guo, Yiming Ying, Ding-Xuan Zhou
Online regularized learning with pairwise loss functions. Adv. Comput. Math. 43 (1) (2017)
Yanbo Fan, Siwei Lyu, Yiming Ying, Bao-Gang Hu
Learning with Average Top-k Loss. NIPS (2017)
Martin Boissier, Siwei Lyu, Yiming Ying, Ding-Xuan Zhou
Fast Convergence of Online Pairwise Learning Algorithms. AISTATS (2016)
Qiong Cao, Zheng-Chu Guo, Yiming Ying
Generalization bounds for metric and similarity learning. Mach. Learn. 102 (1) (2016)
Yiming Ying, Longyin Wen, Siwei Lyu
Stochastic Online AUC Maximization. NIPS (2016)
Yiming Ying, Ding-Xuan Zhou
Online Pairwise Learning Algorithms. Neural Comput. 28 (4) (2016)
Xin Wang, Ming-Ching Chang, Yiming Ying, Siwei Lyu
Co-Regularized PLSA for Multi-Modal Learning. AAAI (2016)
Yiming Ying, Ding-Xuan Zhou
Unregularized Online Learning Algorithms with General Loss Functions. CoRR (2015)
Yiming Ying, Ding-Xuan Zhou
Online Pairwise Learning Algorithms with Kernels. CoRR (2015)
Zheng-Chu Guo, Yiming Ying
Guaranteed Classification via Regularized Similarity Learning. Neural Comput. 26 (3) (2014)
Julien Bohné, Yiming Ying, Stéphane Gentric, Massimiliano Pontil
Large Margin Local Metric Learning. ECCV (2) (2014)
Qiong Cao, Yiming Ying, Peng Li
Similarity Metric Learning for Face Recognition. ICCV (2013)
Zheng-Chu Guo, Yiming Ying
Guaranteed Classification via Regularized Similarity Learning. CoRR (2013)
Qiong Cao, Yiming Ying, Peng Li
Distance Metric Learning Revisited. ECML/PKDD (1) (2012)
Yiming Ying, Qiang Wu, Colin Campbell
Learning the coordinate gradients. Adv. Comput. Math. 37 (3) (2012)
Yiming Ying, Peng Li
Distance Metric Learning with Eigenvalue Optimization. J. Mach. Learn. Res. 13 (2012)
Qiong Cao, Zheng-Chu Guo, Yiming Ying
Generalization Bounds for Metric and Similarity Learning CoRR (2012)
Kaizhu Huang, Yiming Ying, Colin Campbell
Generalized sparse metric learning with relative comparisons. Knowl. Inf. Syst. 28 (1) (2011)
Yiming Ying, Colin Campbell
Rademacher Chaos Complexities for Learning the Kernel Problem. Neural Comput. 22 (11) (2010)
Peng Li, Yiming Ying, Colin Campbell
A Variational Approach to Semi-Supervised Clustering. ESANN (2009)
Yiming Ying, Kaizhu Huang, Colin Campbell
Sparse Metric Learning via Smooth Optimization. NIPS (2009)
Yiming Ying, Colin Campbell, Theodoros Damoulas, Mark A. Girolami
Class Prediction from Disparate Biological Data Sources Using an Iterative Multi-Kernel Algorithm. PRIB (2009)
Kaizhu Huang, Yiming Ying, Colin Campbell
GSML: A Unified Framework for Sparse Metric Learning. ICDM (2009)
Yiming Ying, Colin Campbell
Generalization Bounds for Learning the Kernel Problem. COLT (2009)
Yiming Ying, Colin Campbell, Mark A. Girolami
Analysis of SVM with Indefinite Kernels. NIPS (2009)
Yiming Ying, Kaizhu Huang, Colin Campbell
Enhanced protein fold recognition through a novel data integration approach. BMC Bioinform. 10 (2009)
Theodoros Damoulas, Yiming Ying, Mark A. Girolami, Colin Campbell
Inferring Sparse Kernel Combinations and Relevance Vectors: An Application to Subcellular Localization of Proteins. ICMLA (2008)
Yiming Ying, Colin Campbell
Learning Coordinate Gradients with Multi-Task Kernels. COLT (2008)
Yiming Ying, Massimiliano Pontil
Online Gradient Descent Learning Algorithms. Found. Comput. Math. 8 (5) (2008)

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Publication Activity (10 Years)

Top Topics

Top Venues

Yiming Ying