Federated Averaging

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Period ending 2026-09-14

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Period ending 2026-09-07

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56 papers

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Recovering Physical Parameters from Fragmented Observations via Exact Distributed Spline Merging
Sep 15, 2026Naveen MysoreSparse Observations Sea Surface Temperature
Algorithmic stability via ensembling
Sep 9, 2026Rina Foygel Barber, Richard J. SamworthStability Analysis Privacy-Preserving Framework
Non-Coherent Over-the-Air Federated Learning: Protocol, Convergence, and Device Scheduling
Sep 8, 2026Haifeng Wen, Nicolò Michelusi, Osvaldo Simeone +2Wireless Resource Allocation Wireless Networks
Differentially private federated learning with Byzantine-robust aggregation: A cross-domain framework for secure model training in banking and healthcare systems
Sep 2, 2026Srikumar NayakByzantine-Robust Aggregation Differential Privacy
CRAD: Class-wise Reliability-Aware Distillation for Decentralized Heterogeneous Federated Learning
Aug 31, 2026Baraa Bilbeisi, Mengchen Fan, Baocheng Geng +1One-Shot Federated Learning Heterogeneous Knowledge Distillation
DG-FedReuse: Proxy-Gradient-Gated Cached-Update Reuse with Matched Sparse Uplink Accounting
Aug 5, 2026Rahil Aftab, Vineet Kumar Rakesh, Soumya Mazumdar +1Fedavg Federated Averaging
Learning-Augmented and Randomized Algorithms for Line Aggregation with Delays
Jul 30, 2026Tianhang Lu, Runtian Ren, Shengcai Liu +1Learning-Augmented Algorithms Queueing
Rethinking Heterogeneous LLM Merging: A Weighted Model Averaging Perspective
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Confidence-based Ranking with Adaptive Sampling for Noisy Black-Box Optimisation
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What's in a Smoothness Constant? Tighter Rates for Local SGD with Bounded Second-order Heterogeneity
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Adaptive Runge-Kutta Step Control Buys Training Loss, Not Generalization: An Honest Compute-Matched Study of RK-Adam Optimizers
Jul 16, 2026Akhilesh GogikarAdam Learning Rates
Glob3R: Global Structure-from-Motion with 3D Foundation Models
Jul 10, 2026Junyuan Deng, Heng Li, Kejie Qiu +7Feed-Forward 3D Reconstruction Structure-From-Motion
FedOPAL: One-Shot Federated Learning via Analytic Visual Prompt Tuning
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NFTR: From Provable Mode-Averaging to Geodesic Subgoal Selection in Offline Goal-Conditioned RL
Jul 8, 2026Erdemt Bao, Xing Lei, Jun ChenGoal-Conditioned Reinforcement Learning Reweighting
On the Convergence of Adam, Revisited
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Which Algorithm Specification Formats Help Language Models Implement Machine Learning Algorithms?
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Precomputing the Future-Offset Average in TriAttention
Jul 1, 2026Amarnath MukherjeeKey-Value Cache Prefill
A Single Stepsize Suffices for Unprojected Linear TD(0): Simultaneous Robust and Fast Rates via Polyak--Ruppert Averaging
Jun 23, 2026Wei-Cheng Lee, Francesco OrabonaLarge Step Sizes Temporal Difference
GARIP: A Running-Average Moving Reference for Last-Iterate Self-Play in Two-Player Zero-Sum Games
Jun 21, 2026Can SavcıSelf-Play Optimization Convergence Analysis
Beyond Averaging in John Ellipsoid Approximation: High-Accuracy Algorithms in the Leverage-Score Model
Jun 18, 2026Xiaoyu Li, Junwei Yu, Jiaojiao Jiang +2Optimal Sample Complexity Polytopes
Amortized mean-shift interacting particles
Jun 14, 2026Ali SiahkoohiPosterior Sampling Posterior
Towards Personalized Federated Learning for Dysarthric Speech Recognition
Jun 11, 2026Tao Zhong, Mengzhe Geng, Jiajun Deng +2Dysarthric Speech Speaker Identity
Adaptive Weighted Averaging
Jun 11, 2026Aditya Bhaskara, Ashok Cutkosky, Ravi Kumar +1Stochastic Optimization Federated Averaging
Fed-FBD: Federated Functional Block Diversification for Isolation, Privacy, and Surgical Unlearning
Jun 10, 2026Weijie Chen, Alan B. McMillanPrivacy-Preserving Framework Adversarial Transferability
Privacy-Preserving Federated Autoencoder for ECG Anomaly Detection on Edge Devices
Jun 10, 2026Kaan Arda Akyol, Jakub Kacper Szeląg, Aydin Abadi +9Electrocardiogram Edge Computing
Fast and Robust Convergence Rate for TD(0) with Linear Function Approximation, Universal Learning Steps and I.I.D. Samples
Jun 4, 2026Ziad Kobeissi, Éloïse BerthierTemporal Difference Finite Time Analysis
Beyond Task-Agnostic: Task-Aware Grouping for Communication-Efficient Multi-Task MoE Inference
May 31, 2026Zhiyao Xu, Aoxue Liu, Zhanjie Ding +3Mixture-Of-Expert Inference Multi-Gpu Systems
Q-ANCHOR: Federated Quantum Learning with ZNE-guided Correction
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The Interplay Between Interpolation and Aggregation in Regression: Optimal Sample Complexity
May 28, 2026Mikael Møller Høgsgaard, Kasper Green Larsen, Liang-Yu ZouRegression Interpolation
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May 27, 2026Yuchen Hou, Yongshan Chen, Zhuowen Zou +4Federated Averaging Encoding Models
Hardware-Aware Federated Learning for Speech Emotion Recognition
May 23, 2026Beyazit Bestami Yuksel, Emrah DikbiyikRobust Federated Learning Speech Emotion Recognition
AMUSE: Anytime Muon with Stable Gradient Evaluation
May 21, 2026Jueun Kim, Baekrok Shin, Jihun Yun +3Muon Federated Averaging
An End-to-End PyTorch Interface for Differentiable PDE Solvers: A RANS Model-Correction Study
May 19, 2026Luca Saverio, Michele Alessandro Bucci, Gianmarco Farro +2Partial Differential Equations Shallow Water Equations
Statistical Limits and Efficient Algorithms for Differentially Private Federated Learning
May 18, 2026Arnab Auddy, Xiangni Peng, Subhadeep PaulDifferential Privacy Dp-Sgd
Conflict-Free Replicated Data Types for Neural Network Model Merging: A Two-Layer Architecture Enabling CRDT-Compliant Model Merging Across 26 Strategies
May 16, 2026Ryan GillespieModel Merging Federated Averaging
Bin Latent Transformer (BiLT): A shift-invariant autoencoder for calibration-free spectral unmixing of turbid media
May 12, 2026Martin HohmannSpectra Autoencoder
The Scaling Law of Evaluation Failure: Why Simple Averaging Collapses Under Data Sparsity and Item Difficulty Gaps, and How Item Response Theory Recovers Ground Truth Across Domains
May 11, 2026Jung Min KangItem Response Theory Artificial Intelligence Benchmarks
Optimistic Dual Averaging Unifies Modern Optimizers
May 11, 2026Thomas Pethick, Wanyun Xie, Roman Machacek +1Adaptive Optimizers Federated Averaging
Aggregation in conformal e-classification
May 8, 2026Vladimir VovkConformal Prediction Conformal Selection
Refining Compositional Diffusion for Reliable Long-Horizon Planning
May 4, 2026Kyowoon Lee, Yunhao Luo, Anh Tong +1Diffusion Planning Long-Horizon Planning
Higher-Order Flexible Configurations of Planar Parallel Manipulators Constructed by Averaging
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Generalizing the Geometry of Model Merging Through Frechet Averages
Apr 29, 2026Marvin F. da Silva, Mohammed Adnan, Felix Dangel +1Continual Model Merging Model Merging
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Apr 27, 2026Olav Benjamin VassendBregman Divergences Federated Averaging
FedSPDnet: Geometry-Aware Federated Deep Learning with SPDnet
Apr 24, 2026Thibault Pautrel, Florent Bouchard, Ammar Mian +1Federated Learning Framework Fedavg
Shard the Gradient, Scale the Model: Serverless Federated Aggregation via Gradient Partitioning
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Federated Rule Ensemble Method in Medical Data
Apr 20, 2026Ke Wan, Kensuke Tanioka, Toshio ShimokawaFederated Learning Framework Federated Averaging
Rethinking Cross-Dose PET Denoising: Mitigating Averaging Effects via Residual Noise Learning
Apr 18, 2026Yichao Liu, Zongru Shao, Yueyang Teng +1Positron Emission Tomography Noise-Aware
Curvature-Aligned Probing for Local Loss-Landscape Stabilization
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Sliding-Window Reordering with Overlap Averaging: A Simple Time-Domain Augmentation for Multivariate Forecasting
Apr 10, 2026Jafar Bakhshaliyev, Johannes Burchert, Niels Landwehr +1Time Series Forecasting Data Augmentation
Algebraic Diversity: Group-Theoretic Spectral Estimation from Single Observations
Apr 4, 2026Mitchell A. ThorntonBeamforming Covariance Estimation
Mechanistic Evidence for Preserved-but-Misaligned Representations in Non-IID FedAvg
Dec 28, 2025Muhammad Haseeb, Salaar Masood, Muhammad Abdullah Sohail +2Federated Averaging Representation Learning
Formal Bayesian Transfer Learning via the Total Risk Prior
Jul 31, 2025Nathan Wycoff, Ali Arab, Lisa O. SinghEmpirical Risk Minimization Lasso
SEMA: a Scalable and Efficient Mamba like Attention via Token Localization and Averaging
Jun 10, 2025Nhat Thanh Tran, Fanghui Xue, Shuai Zhang +4Spatial Reverse Mamba Attention Network Mamba-Based Models
Never Skip a Batch: Dense Learning of Temporal GNNs via Adaptive Pseudo-Supervision
May 18, 2025Alexander Panyshev, Dmitry Vinichenko, Oleg Travkin +2Temporal Graph Neural Networks Batch Size
Statistical Inference for Policy Evaluation with Temporal Difference Learning
Oct 21, 2024Weichen Wu, Gen Li, Yuting Wei +1Temporal Difference Value Functions

Sep 15, 2026 · cs.LGJ/K move · Enter open · S save

Recovering Physical Parameters from Fragmented Observations via Exact Distributed Spline Merging

Naveen Mysore

Scientific measurements are frequently distributed across locations, time periods, and institutions. Combining such fragments into a continuous, differentiable field enables recovering governing physical parameters from its derivatives. This paper makes two contributions toward that goal. First, the established additive structure of fixed-basis ridge-regression statistics is applied to tensor-product spline fields: each data holder computes a local Gram matrix and moment vector, and the merged solution is mathematically identical to centralized fitting, with no raw data shared and no iterative synchronization. This property is specific to the fixed-feature squared-error setting; the present derivation does not establish an analogous guarantee for general jointly trained multilayer networks. Second, a complete pipeline connects distributed observations to physical parameter inference through field reconstruction, derivative extraction, and linear regression. The diffusion coefficient is recovered to 0.11% error and wave speed to 0.12% error; in both cases, distributed merging introduces zero degradation relative to centralized fitting. Application to 41 years of NOAA sea-surface temperature data confirms the result on real spatiotemporal observations.

Sparse Observations Sea Surface Temperature Federated Averaging

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