Lingzhou Xue - RankMe

50 papers A* 5A 1Journal 40Unranked 4

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	EXACT: Explicit Attribute-Guided Decoding-Time Personalization. CoRR Xin Yu, Hanwen Xing, Lingzhou Xue
2026	J	`jnl`	Gap-Dependent Bounds for Nearly Minimax Optimal Reinforcement Learning with Linear Function Approximation. CoRR Haochen Zhang, Zhong Zheng, Lingzhou Xue
2025	J	`jnl`	A Graphical Point Process Framework for Understanding Removal Effects in Multi-Touch Attribution. Manag. Sci. Jun Tao, Qian Chen, James W. Snyder Jr., Arava Sai Kumar, Amirhossein Meisami, Lingzhou Xue
2025	J	`jnl`	AltLoRA: Towards Better Gradient Approximation in Low-Rank Adaptation with Alternating Projections. CoRR Xin Yu, Yujia Wang, Jinghui Chen, Lingzhou Xue
2025	J	`jnl`	Clustering Time-Evolving Networks Using Temporal Exponential-Family Random Graph Models with Conditional Dyadic Independence and Dynamic Latent Blocks. J. Comput. Graph. Stat. Amal Agarwal, Kevin H. Lee, Lingzhou Xue
2025	J	`jnl`	Composition-on-composition regression analysis for multi-omics integration of metagenomic data. Bioinform. Nicholas Rios, Yuke Shi, Jun Chen, Xiang Zhan, Lingzhou Xue, Qizhai Li
2025	A*	`conf`	Federated Q-Learning with Reference-Advantage Decomposition: Almost Optimal Regret and Logarithmic Communication Cost. ICLR Zhong Zheng, Haochen Zhang, Lingzhou Xue
2025	J	`jnl`	Gap-Dependent Bounds for Federated CoRR Haochen Zhang, Zhong Zheng, Lingzhou Xue
2025	A*	`conf`	Gap-Dependent Bounds for Federated Q-Learning. ICML Haochen Zhang, Zhong Zheng, Lingzhou Xue
2025	A*	`conf`	Gap-Dependent Bounds for Q-Learning using Reference-Advantage Decomposition. ICLR Zhong Zheng, Haochen Zhang, Lingzhou Xue
2025	J	`jnl`	PrunedLoRA: Robust Gradient-Based structured pruning for Low-rank Adaptation in Fine-tuning. CoRR Xin Yu, Cong Xie, Ziyu Zhao, Tiantian Fan, Lingzhou Xue, Zhi Zhang
2025	J	`jnl`	Q-Learning with Fine-Grained Gap-Dependent Regret. CoRR Haochen Zhang, Zhong Zheng, Lingzhou Xue
2025	J	`jnl`	Regret-Optimal Q-Learning with Low Cost for Single-Agent and Federated Reinforcement Learning. CoRR Haochen Zhang, Zhong Zheng, Lingzhou Xue
2025	J	`jnl`	Theoretical Guarantees for Sparse Principal Component Analysis Based on the Elastic Net. IEEE Trans. Inf. Theory Haoyi Yang, Teng Zhang, Lingzhou Xue
2025	A*	`conf`	Understanding the Statistical Accuracy-Communication Trade-off in Personalized Federated Learning with Minimax Guarantees. ICML Xin Yu, Zelin He, Ying Sun, Lingzhou Xue, Runze Li
2024	J	`jnl`	A Copula Graphical Model for Multi-Attribute Data using Optimal Transport. CoRR Qi Zhang, Bing Li, Lingzhou Xue
2024	J	`jnl`	A New Inexact Proximal Linear Algorithm With Adaptive Stopping Criteria for Robust Phase Retrieval. IEEE Trans. Signal Process. Zhong Zheng, Shiqian Ma, Lingzhou Xue
2024	J	`jnl`	Federated Q-Learning with Reference-Advantage Decomposition: Almost Optimal Regret and Logarithmic Communication Cost. CoRR Zhong Zheng, Haochen Zhang, Lingzhou Xue
2024	A*	`conf`	Federated Q-Learning: Linear Regret Speedup with Low Communication Cost. ICLR Zhong Zheng, Fengyu Gao, Lingzhou Xue, Jing Yang
2024	J	`jnl`	Gap-Dependent Bounds for Q-Learning using Reference-Advantage Decomposition. CoRR Zhong Zheng, Haochen Zhang, Lingzhou Xue
2024	J	`jnl`	Nonlinear sufficient dimension reduction for distribution-on-distribution regression. J. Multivar. Anal. Qi Zhang, Bing Li, Lingzhou Xue
2024	J	`jnl`	Smoothed Robust Phase Retrieval. CoRR Zhong Zheng, Lingzhou Xue
2024	J	`jnl`	The Effect of Personalization in FedProx: A Fine-grained Analysis on Statistical Accuracy and Communication Efficiency. CoRR Xin Yu, Zelin He, Ying Sun, Lingzhou Xue, Runze Li
2023	J	`jnl`	A Graphical Point Process Framework for Understanding Removal Effects in Multi-Touch Attribution. CoRR Jun Tao, Qian Chen, James W. Snyder Jr., Arava Sai Kumar, Amirhossein Meisami, Lingzhou Xue
2023	J	`jnl`	A New Inexact Proximal Linear Algorithm with Adaptive Stopping Criteria for Robust Phase Retrieval. CoRR Zhong Zheng, Shiqian Ma, Lingzhou Xue
2023	J	`jnl`	Federated Q-Learning: Linear Regret Speedup with Low Communication Cost. CoRR Zhong Zheng, Fengyu Gao, Lingzhou Xue, Jing Yang
2023	J	`jnl`	Identification of microbial features in multivariate regression under false discovery rate control. Comput. Stat. Data Anal. Arun Srinivasan, Lingzhou Xue, Xiang Zhan
2022	J	`jnl`	A Manifold Proximal Linear Method for Sparse Spectral Clustering with Application to Single-Cell RNA Sequencing Data Analysis. INFORMS J. Optim. Zhongruo Wang, Bingyuan Liu, Shixiang Chen, Shiqian Ma, Lingzhou Xue, Hongyu Zhao
2022	J	`jnl`	Improving neural network robustness through neighborhood preserving layers. Image Vis. Comput. Bingyuan Liu, Christopher Malon, Lingzhou Xue, Erik Kruus
2022	J	`jnl`	Riemannian Stochastic Proximal Gradient Methods for Nonsmooth Optimization over the Stiefel Manifold. J. Mach. Learn. Res. Bokun Wang, Shiqian Ma, Lingzhou Xue
2021	J	`jnl`	An additive graphical model for discrete data. CoRR Jun Tao, Bing Li, Lingzhou Xue
2021	J	`jnl`	Improving Neural Network Robustness through Neighborhood Preserving Layers. CoRR Bingyuan Liu, Christopher Malon, Lingzhou Xue, Erik Kruus
2020	J	`jnl`	A Manifold Proximal Linear Method for Sparse Spectral Clustering with Application to Single-Cell RNA Sequencing Data Analysis. CoRR Zhongruo Wang, Bingyuan Liu, Shixiang Chen, Shiqian Ma, Lingzhou Xue, Hongyu Zhao
2020	J	`jnl`	An Alternating Manifold Proximal Gradient Method for Sparse Principal Component Analysis and Sparse Canonical Correlation Analysis. INFORMS J. Optim. Shixiang Chen, Shiqian Ma, Lingzhou Xue, Hui Zou
2020	—	`conf`	Hawkesian Graphical Event Models. PGM Xiufan Yu, Karthikeyan Shanmugam, Debarun Bhattacharjya, Tian Gao, Dharmashankar Subramanian, Lingzhou Xue
2020	—	`conf`	Improving Neural Network Robustness Through Neighborhood Preserving Layers. ICPR Workshops (6) Bingyuan Liu, Christopher Malon, Lingzhou Xue, Erik Kruus
2020	J	`jnl`	Model-Based Clustering of Nonparametric Weighted Networks With Application to Water Pollution Analysis. Technometrics Amal Agarwal, Lingzhou Xue
2020	J	`jnl`	Model-based clustering of time-evolving networks through temporal exponential-family random graph models. J. Multivar. Anal. Kevin H. Lee, Lingzhou Xue, David R. Hunter
2020	J	`jnl`	Riemannian Stochastic Proximal Gradient Methods for Nonsmooth Optimization over the Stiefel Manifold. CoRR Bokun Wang, Shiqian Ma, Lingzhou Xue
2019	J	`jnl`	An Alternating Manifold Proximal Gradient Method for Sparse PCA and Sparse CCA. CoRR Shixiang Chen, Shiqian Ma, Lingzhou Xue, Hui Zou
2018	J	`jnl`	A Selective Overview of Sparse Principal Component Analysis. Proc. IEEE Hui Zou, Lingzhou Xue
2018	J	`jnl`	Condition-adaptive fused graphical lasso (CFGL): An adaptive procedure for inferring condition-specific gene co-expression network. PLoS Comput. Biol. Yafei Lyu, Lingzhou Xue, Feipeng Zhang, Hillary Koch, Laura M. Saba, Katerina J. Kechris, Qunhua Li
2018	J	`jnl`	Nonparametric Finite Mixture of Gaussian Graphical Models. Technometrics Kevin H. Lee, Lingzhou Xue
2017	A	`conf`	Discovery of Causal Time Intervals. SDM Zhenhui Li, Guanjie Zheng, Amal Agarwal, Lingzhou Xue, Thomas Lauvaux
2017	J	`jnl`	Model-Based Clustering of Nonparametric Weighted Networks. CoRR Amal Agarwal, Lingzhou Xue
2017	J	`jnl`	Model-Based Clustering of Time-Evolving Networks through Temporal Exponential-Family Random Graph Models. CoRR Kevin H. Lee, Lingzhou Xue, David R. Hunter
2013	J	`jnl`	Alternating Direction Methods for Latent Variable Gaussian Graphical Model Selection. Neural Comput. Shiqian Ma, Lingzhou Xue, Hui Zou
2013	J	`jnl`	Minimax optimal estimation of general bandable covariance matrices. J. Multivar. Anal. Lingzhou Xue, Hui Zou
2007	—	`conf`	A Novel Real Time Method of Signal Strength Based Indoor Localization. ICCSA (1) Letian Ye, Zhi Geng, Lingzhou Xue, Zhihai Liu
2007	—	`conf`	A gradually locating method of indoor locating estimation based on likelihood. Mobility Conference Letian Ye, Zhihai Liu, Lingzhou Xue, Ping He, Zhi Geng