Wang, Shiqiang

27 publications

ICLR 2025 Dynamic Loss-Based Sample Reweighting for Improved Large Language Model Pretraining Daouda Sow, Herbert Woisetschläger, Saikiran Bulusu, Shiqiang Wang, Hans Arno Jacobsen, Yingbin Liang

NeurIPS 2025 Flick: Empowering Federated Learning with Commonsense Knowledge Ran Zhu, Mingkun Yang, Shiqiang Wang, Jie Yang, Qing Wang

NeurIPS 2025 MESS+: Dynamically Learned Inference-Time LLM Routing in Model Zoos with Service Level Guarantees Herbert Woisetschläger, Ryan Zhang, Shiqiang Wang, Hans Arno Jacobsen

NeurIPS 2025 RCCDA: Adaptive Model Updates in the Presence of Concept Drift Under a Constrained Resource Budget Adam Piaseczny, Md Kamran Chowdhury Shisher, Shiqiang Wang, Christopher Brinton

ICLR 2025 Vertical Federated Learning with Missing Features During Training and Inference Pedro Valdeira, Shiqiang Wang, Yuejie Chi

ICLR 2024 A Lightweight Method for Tackling Unknown Participation Statistics in Federated Averaging Shiqiang Wang, Mingyue Ji

ICML 2024 A New Theoretical Perspective on Data Heterogeneity in Federated Optimization Jiayi Wang, Shiqiang Wang, Rong-Rong Chen, Mingyue Ji

IJCAI 2024 A Survey on Efficient Federated Learning Methods for Foundation Model Training Herbert Woisetschläger, Alexander Erben, Shiqiang Wang, Ruben Mayer, Hans-Arno Jacobsen

AAAI 2024 DePRL: Achieving Linear Convergence Speedup in Personalized Decentralized Learning with Shared Representations Guojun Xiong, Gang Yan, Shiqiang Wang, Jian Li

ICML 2024 FADAS: Towards Federated Adaptive Asynchronous Optimization Yujia Wang, Shiqiang Wang, Songtao Lu, Jinghui Chen

AISTATS 2024 FedFisher: Leveraging Fisher Information for One-Shot Federated Learning Divyansh Jhunjhunwala, Shiqiang Wang, Gauri Joshi

NeurIPS 2024 Hierarchical Federated Learning with Multi-Timescale Gradient Correction Wenzhi Fang, Dong-Jun Han, Evan Chen, Shiqiang Wang, Christopher G. Brinton

NeurIPSW 2024 MESS+: Energy-Optimal Inferencing in Language Model Zoos with Service Level Guarantees Ryan Zhang, Herbert Woisetschläger, Shiqiang Wang, Hans Arno Jacobsen

ICMLW 2023 A New Theoretical Perspective on Data Heterogeneity in Federated Optimization Jiayi Wang, Shiqiang Wang, Rong-Rong Chen, Mingyue Ji

ICLR 2023 FedExP: Speeding up Federated Averaging via Extrapolation Divyansh Jhunjhunwala, Shiqiang Wang, Gauri Joshi

CVPR 2023 Gradient-Based Uncertainty Attribution for Explainable Bayesian Deep Learning Hanjing Wang, Dhiraj Joshi, Shiqiang Wang, Qiang Ji

ICML 2023 LESS-VFL: Communication-Efficient Feature Selection for Vertical Federated Learning Timothy Castiglia, Yi Zhou, Shiqiang Wang, Swanand Kadhe, Nathalie Baracaldo, Stacy Patterson

NeurIPS 2023 StableFDG: Style and Attention Based Learning for Federated Domain Generalization Jungwuk Park, Dong-Jun Han, Jinho Kim, Shiqiang Wang, Christopher Brinton, Jaekyun Moon

ICMLW 2023 Towards a Theoretical and Practical Understanding of One-Shot Federated Learning with Fisher Information Divyansh Jhunjhunwala, Shiqiang Wang, Gauri Joshi

NeurIPS 2022 A Unified Analysis of Federated Learning with Arbitrary Client Participation Shiqiang Wang, Mingyue Ji

ICML 2022 Compressed-VFL: Communication-Efficient Learning with Vertically Partitioned Data Timothy J Castiglia, Anirban Das, Shiqiang Wang, Stacy Patterson

AAAI 2022 Demystifying Why Local Aggregation Helps: Convergence Analysis of Hierarchical SGD Jiayi Wang, Shiqiang Wang, Rong-Rong Chen, Mingyue Ji

AAAI 2022 KerGNNs: Interpretable Graph Neural Networks with Graph Kernels Aosong Feng, Chenyu You, Shiqiang Wang, Leandros Tassiulas

NeurIPSW 2022 Self-Supervised Vertical Federated Learning Timothy Castiglia, Shiqiang Wang, Stacy Patterson

ALT 2021 Online Learning of Facility Locations Stephen Pasteris, Ting He, Fabio Vitale, Shiqiang Wang, Mark Herbster

NeurIPS 2020 Online Algorithms for Multi-Shop Ski Rental with Machine Learned Advice Shufan Wang, Jian Li, Shiqiang Wang

AISTATS 2019 MaxHedge: Maximizing a Maximum Online Stephen Pasteris, Fabio Vitale, Kevin Chan, Shiqiang Wang, Mark Herbster