Xin Zhang

According to our database, Xin Zhang authored at least 41 papers between 2013 and 2026.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2026

TeleWorld: Towards Dynamic Multimodal Synthesis with a 4D World Model.

Yabo Chen, Yuanzhi Liang, Jiepeng Wang, Tingxi Chen, Junfei Cheng, Zixiao Gu, Yuyang Huang, Zicheng Jiang, Wei Li, Tian Li, Weichen Li, Zuoxin Li, Guangce Liu, Jialun Liu, Junqi Liu, Haoyuan Wang, Qizhen Weng, Xuan'er Wu, Xunzhi Xiang, Xiaoyan Yang, Xin Zhang, Shiwen Zhang, Junyu Zhou, Chengcheng Zhou, Haibin Huang, Chi Zhang, Xuelong Li

CoRR, January, 2026

Multi-Objective Bilevel Learning.

Zhiyao Zhang, Zhuqing Liu, Xin Zhang, Wen-Yen Chen, Jiyan Yang, Jia Liu

Proceedings of the Fortieth AAAI Conference on Artificial Intelligence, 2026

2025

Beyond Aggregation: Guiding Clients in Heterogeneous Federated Learning.

Zijian Wang, Xiaofei Zhang, Xin Zhang, Yukun Liu, Qiong Zhang

CoRR, September, 2025

Two-dimensional Sparse Parallelism for Large Scale Deep Learning Recommendation Model Training.

Xin Zhang, Quanyu Zhu, Liangbei Xu, Zain Huda, Wang Zhou, Jin Fang, Dennis van der Staay, Yuxi Hu, Jade Nie, Jiyan Yang, Chunzhi Yang

CoRR, August, 2025

External Large Foundation Model: How to Efficiently Serve Trillions of Parameters for Online Ads Recommendation.

Mingfu Liang, Xi Liu, Rong Jin, Boyang Liu, Qiuling Suo, Qinghai Zhou, Song Zhou, Laming Chen, Hua Zheng, Zhiyuan Li, Shali Jiang, Jiyan Yang, Xiaozhen Xia, Fan Yang, Yasmine Badr, Ellie Wen, Shuyu Xu, Hansey Chen, Zhengyu Zhang, Jade Nie, Chunzhi Yang, Zhichen Zeng, Weilin Zhang, Xingliang Huang, Qianru Li, Shiquan Wang, Evelyn Lyu, Wenjing Lu, Rui Zhang, Wenjun Wang, Jason Rudy, Mengyue Hang, Kai Wang, Yinbin Ma, Shuaiwen Wang, Sihan Zeng, Tongyi Tang, Xiaohan Wei, Longhao Jin, Jamey Zhang, Marcus Chen, Jiayi Zhang, Angie Huang, Chi Zhang, Zhengli Zhao, Jared Yang, Qiang Jin, Xian Chen, Amit Anand Amlesahwaram, Lexi Song, Liang Luo, Yuchen Hao, Nan Xiao, Yavuz Yetim, Luoshang Pan, Gaoxiang Liu, Yuxi Hu, Yuzhen Huang, Jackie Xu, Rich Zhu, Xin Zhang, Yiqun Liu, Hang Yin, Yuxin Chen, Buyun Zhang, Xiaoyi Liu, Xingyuan Wang, Wenguang Mao, Zhijing Li, Qin Huang, Chonglin Sun, Shupin Mao, Benjamin Au, Jingzheng Qin, Peggy Yao, Jae-Woo Choi, Bin Gao, Ernest Wang, Lei Zhang, Wen-Yen Chen, Ted Lee, Jay Zha, Yi Meng, Alex Gong, Edison Gao, Alireza Vahdatpour, Yiping Han, Yantao Yao, Toshinari Kureha, Shuo Chang, Musharaf Sultan, John Bocharov, Sagar Chordia, Xiaorui Gan, Peng Sun, Rocky Liu, Bo Long, Wenlin Chen, Santanu Kolay, Huayu Li

CoRR, February, 2025

Personalized Interpolation: An Efficient Method to Tame Flexible Optimization Window Estimation.

Xin Zhang, Weiliang Li, Rui Li, Zihang Fu, Tongyi Tang, Zhengyu Zhang, Wen-Yen Chen, Nima Noorshams, Nirav Jasapara, Xiaowen Ding, Ellie Wen, Xue Feng

CoRR, January, 2025

Spatial Heterogeneous Additive Partial Linear Model: A Joint Approach of Bivariate Spline and Forest Lasso.

Xin Zhang, Shan Yu, Zhengyuan Zhu, Xin Wang

J. Comput. Graph. Stat., 2025

Simultaneously detecting spatiotemporal changes with penalized Poisson regression models.

Zerui Zhang, Xin Wang, Xin Zhang, Jing Zhang

Comput. Stat. Data Anal., 2025

InterFormer: Effective Heterogeneous Interaction Learning for Click-Through Rate Prediction.

Zhichen Zeng, Xiaolong Liu, Mengyue Hang, Xiaoyi Liu, Qinghai Zhou, Chaofei Yang, Yiqun Liu, Yichen Ruan, Laming Chen, Yuxin Chen, Yujia Hao, Jiaqi Xu, Jade Nie, Xi Liu, Buyun Zhang, Wei Wen, Siyang Yuan, Hang Yin, Xin Zhang, Kai Wang, Wen-Yen Chen, Yiping Han, Huayu Li, Chunzhi Yang, Bo Long, Philip S. Yu, Hanghang Tong, Jiyan Yang

Proceedings of the 34th ACM International Conference on Information and Knowledge Management, 2025

2024

Efficient Sparse Least Absolute Deviation Regression With Differential Privacy.

Weidong Liu, Xiaojun Mao, Xiaofei Zhang, Xin Zhang

IEEE Trans. Inf. Forensics Secur., 2024

Rankitect: Ranking Architecture Search Battling World-class Engineers at Meta Scale.

Wei Wen, Kuang-Hung Liu, Igor Fedorov, Xin Zhang, Hang Yin, Weiwei Chu, Kaveh Hassani, Mengying Sun, Jiang Liu, Xu Wang, Lin Jiang, Yuxin Chen, Buyun Zhang, Xi Liu, Dehua Cheng, Zhengxing Chen, Guang Zhao, Fangqiu Han, Jiyan Yang, Yuchen Hao, Liang Xiong, Wen-Yen Chen

Proceedings of the Companion Proceedings of the ACM on Web Conference 2024, 2024

Local Superior Soups: A Catalyst for Model Merging in Cross-Silo Federated Learning.

Minghui Chen, Meirui Jiang, Xin Zhang, Qi Dou, Zehua Wang, Xiaoxiao Li

Proceedings of the Advances in Neural Information Processing Systems 37: Annual Conference on Neural Information Processing Systems 2024, 2024

SiGeo: Sub-One-Shot NAS via Geometry of Loss Landscape.

Hua Zheng, Kuang-Hung Liu, Igor Fedorov, Xin Zhang, Wen-Yen Chen, Wei Wen

Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2024

Overcoming Data and Model heterogeneities in Decentralized Federated Learning via Synthetic Anchors.

Chun-Yin Huang, Kartik Srinivas, Xin Zhang, Xiaoxiao Li

Proceedings of the Forty-first International Conference on Machine Learning, 2024

PILOT: An $\mathcal{O}(1/K)$-Convergent Approach for Policy Evaluation with Nonlinear Function Approximation.

Zhuqing Liu, Xin Zhang, Jia Liu, Zhengyuan Zhu, Songtao Lu

Proceedings of the Twelfth International Conference on Learning Representations, 2024

ReTaSA: A Nonparametric Functional Estimation Approach for Addressing Continuous Target Shift.

Hwanwoo Kim, Xin Zhang, Jiwei Zhao, Qinglong Tian

Proceedings of the Twelfth International Conference on Learning Representations, 2024

2023

Clustered Coefficient Regression Models for Poisson Process with an Application to Seasonal Warranty Claim Data.

Xin Wang, Xin Zhang, Zhengyuan Zhu

Technometrics, October, 2023

SiGeo: Sub-One-Shot NAS via Information Theory and Geometry of Loss Landscape.

Hua Zheng, Kuang-Hung Liu, Igor Fedorov, Xin Zhang, Wen-Yen Chen, Wei Wen

CoRR, 2023

PRECISION: Decentralized Constrained Min-Max Learning with Low Communication and Sample Complexities.

Zhuqing Liu, Xin Zhang, Songtao Lu, Jia Liu

Proceedings of the Twenty-fourth International Symposium on Theory, 2023

ELSA: Efficient Label Shift Adaptation through the Lens of Semiparametric Models.

Qinglong Tian, Xin Zhang, Jiwei Zhao

Proceedings of the International Conference on Machine Learning, 2023

Prometheus: Taming Sample and Communication Complexities in Constrained Decentralized Stochastic Bilevel Learning.

Zhuqing Liu, Xin Zhang, Prashant Khanduri, Songtao Lu, Jia Liu

Proceedings of the International Conference on Machine Learning, 2023

2022

Fast and Robust Sparsity Learning Over Networks: A Decentralized Surrogate Median Regression Approach.

Weidong Liu, Xiaojun Mao, Xin Zhang

IEEE Trans. Signal Process., 2022

SAGDA: Achieving O(ε^-2) Communication Complexity in Federated Min-Max Learning.

Haibo Yang, Zhuqing Liu, Xin Zhang, Jia Liu

CoRR, 2022

SAGDA: Achieving $\mathcal{O}(\epsilon^{-2})$ Communication Complexity in Federated Min-Max Learning.

Haibo Yang, Zhuqing Liu, Xin Zhang, Jia Liu

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

NET-FLEET: achieving linear convergence speedup for fully decentralized federated learning with heterogeneous data.

Xin Zhang, Minghong Fang, Zhuqing Liu, Haibo Yang, Jia Liu, Zhengyuan Zhu

Proceedings of the MobiHoc '22: The Twenty-third International Symposium on Theory, Algorithmic Foundations, and Protocol Design for Mobile Networks and Mobile Computing, Seoul, Republic of Korea, October 17, 2022

SYNTHESIS: a semi-asynchronous path-integrated stochastic gradient method for distributed learning in computing clusters.

Zhuqing Liu, Xin Zhang, Jia Liu

Proceedings of the MobiHoc '22: The Twenty-third International Symposium on Theory, Algorithmic Foundations, and Protocol Design for Mobile Networks and Mobile Computing, Seoul, Republic of Korea, October 17, 2022

INTERACT: achieving low sample and communication complexities in decentralized bilevel learning over networks.

Zhuqing Liu, Xin Zhang, Prashant Khanduri, Songtao Lu, Jia Liu

Proceedings of the MobiHoc '22: The Twenty-third International Symposium on Theory, Algorithmic Foundations, and Protocol Design for Mobile Networks and Mobile Computing, Seoul, Republic of Korea, October 17, 2022

Anarchic Federated Learning.

Haibo Yang, Xin Zhang, Prashant Khanduri, Jia Liu

Proceedings of the International Conference on Machine Learning, 2022

2021

Taming Communication and Sample Complexities in Decentralized Policy Evaluation for Cooperative Multi-Agent Reinforcement Learning.

Xin Zhang, Zhuqing Liu, Jia Liu, Zhengyuan Zhu, Songtao Lu

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

GT-STORM: Taming Sample, Communication, and Memory Complexities in Decentralized Non-Convex Learning.

Xin Zhang, Jia Liu, Zhengyuan Zhu, Elizabeth Serena Bentley

Proceedings of the MobiHoc '21: The Twenty-second International Symposium on Theory, 2021

Low Sample and Communication Complexities in Decentralized Learning: A Triple Hybrid Approach.

Xin Zhang, Jia Liu, Zhengyuan Zhu, Elizabeth Serena Bentley

Proceedings of the 40th IEEE Conference on Computer Communications, 2021

2020

Adaptive Multi-Hierarchical signSGD for Communication-Efficient Distributed Optimization.

Haibo Yang, Xin Zhang, Minghong Fang, Jia Liu

Proceedings of the 21st IEEE International Workshop on Signal Processing Advances in Wireless Communications, 2020

Private and communication-efficient edge learning: a sparse differential gaussian-masking distributed SGD approach.

Xin Zhang, Minghong Fang, Jia Liu, Zhengyuan Zhu

Proceedings of the Mobihoc '20: The Twenty-first ACM International Symposium on Theory, 2020

Communication-Efficient Network-Distributed Optimization with Differential-Coded Compressors.

Xin Zhang, Jia Liu, Zhengyuan Zhu, Elizabeth S. Bentley

Proceedings of the 39th IEEE Conference on Computer Communications, 2020

Taming Convergence for Asynchronous Stochastic Gradient Descent with Unbounded Delay in Non-Convex Learning.

Xin Zhang, Jia Liu, Zhengyuan Zhu

Proceedings of the 59th IEEE Conference on Decision and Control, 2020

2019

Distributed Linear Model Clustering over Networks: A Tree-Based Fused-Lasso ADMM Approach.

Xin Zhang, Jia Liu, Zhengyuan Zhu

CoRR, 2019

Spatial CUSUM for Signal Region Detection.

Xin Zhang, Zhengyuan Zhu

CoRR, 2019

Compressed Distributed Gradient Descent: Communication-Efficient Consensus over Networks.

Xin Zhang, Jia Liu, Zhengyuan Zhu, Elizabeth S. Bentley

Proceedings of the 2019 IEEE Conference on Computer Communications, 2019

Byzantine-Resilient Stochastic Gradient Descent for Distributed Learning: A Lipschitz-Inspired Coordinate-wise Median Approach.

Haibo Yang, Xin Zhang, Minghong Fang, Jia Liu

Proceedings of the 58th IEEE Conference on Decision and Control, 2019

2017

Drug-target interaction prediction by integrating multiview network data.

Xin Zhang, Limin Li, Michael K. Ng, Shuqin Zhang

Comput. Biol. Chem., 2017

2013

Fast Approximate Matching Algorithm for Phone-based Keyword Spotting.

Xin Zhang, Meng Cai, Jia Liu

J. Networks, 2013