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Zhenyu Sun

7 accepted papers

2025

Debiasing Federated Learning with Correlated Client Participation

ICLR 2025poster

In cross-device federated learning (FL) with millions of mobile clients, only a small subset of clients participate in training in every communication round, and Federated Averaging (FedAvg) is the most popular algorithm in practice. Existing analyses of FedAvg usually assume the participating clie…

Cited by 0SourcePDFScholar
2025

Improved Lower Bounds for First-order Stochastic Non-convex Optimization under Markov Sampling

ICML 2025poster

Unlike its vanilla counterpart with i.i.d. samples, stochastic optimization with Markovian sampling allows the sampling scheme following a Markov chain. This problem encompasses various applications that range from asynchronous distributed optimization to reinforcement learning. In this work, we low…

Cited by 0SourcePDFScholar
2025

Toy-GS: Assembling Local Gaussians for Precisely Rendering Large-Scale Free Camera Trajectories

AAAI 2025technical

Currently, 3D rendering for large-scale free camera trajectories, namely, arbitrary input camera trajectories, poses significant challenges: 1) The distribution and observation angles of the cameras are irregular, and various types of scenes are included in the free trajectories; 2) Processing the e…

2024

Understanding Generalization of Federated Learning via Stability: Heterogeneity Matters

AISTATS 2024poster

Generalization performance is a key metric in evaluating machine learning models when applied to real-world applications. Good generalization indicates the model can predict unseen data correctly when trained under a limited number of data. Federated learning (FL), which has emerged as a popular dis…

Cited by 28SourcePDFScholar
2022

A Communication-efficient Algorithm with Linear Convergence for Federated Minimax Learning

NeurIPS 2022accept

In this paper, we study a large-scale multi-agent minimax optimization problem, which models many interesting applications in statistical learning and game theory, including Generative Adversarial Networks (GANs). The overall objective is a sum of agents' private local objective functions. We focus…

Cited by 18SourcePDFScholar
2021

Enhanced Language Representation with Label Knowledge for Span Extraction

EMNLP 2021main

Span extraction, aiming to extract text spans (such as words or phrases) from plain text, is a fundamental process in Information Extraction. Recent works introduce the label knowledge to enhance the text representation by formalizing the span extraction task into a question answering problem (QA Fo…