Local Model

Local models in machine learning focus on training individual models on subsets of data, often within decentralized or federated learning frameworks, to address data heterogeneity and privacy concerns. Current research emphasizes techniques like neural tangent kernels for improved convergence and model averaging to enhance accuracy in heterogeneous settings, along with personalized federated learning approaches using Bayesian optimization, mixture-of-experts models, and adaptive parameter selection to tailor models to individual data distributions. This research is significant for improving the efficiency and robustness of machine learning in diverse and privacy-sensitive applications, such as healthcare, personalized recommendations, and collaborative model training across multiple institutions.

Papers

November 22, 2023

A Joint Gradient and Loss Based Clustered Federated Learning Design
Licheng Lin, Mingzhe Chen, Zhaohui Yang, Yusen Wu, Yuchen Liu
Joint Optimization Interest Loss Local Model Clustered Federated Learning FL Algorithm Efficient Clustering

November 12, 2023

pFedES: Model Heterogeneous Personalized Federated Learning with Feature Extractor Sharing
Liping Yi, Han Yu, Gang Wang, Xiaoguang Liu
Privacy Preserving Local Model Feature Extractor Federated Learning Approach Local Heterogeneous Model

November 8, 2023

Decentralized Personalized Online Federated Learning
Renzhi Wu, Saayan Mitra, Xiang Chen, Anup Rao
Personalized Federated Learning Local Model Personalized Model Recommendation Datasets

November 6, 2023

Grouping Local Process Models
Viki Peeva, Wil M. P. van der Aalst
Process Mining Local Model Process Discovery

October 20, 2023

October 13, 2023

PAGE: Equilibrate Personalization and Generalization in Federated Learning
Qian Chen, Zilong Wang, Jiaqi Hu, Haonan Yan, Jianying Zhou, Xiaodong Lin
Strong Generalization Reinforcement Learning Algorithm Global Model Local Model Web Page

September 26, 2023

PLMM: Personal Large Language Models on Mobile Devices
Yuanhao Gong
Large Language Model Large Model Mobile Device Local Model Expert Model PLM Based

August 14, 2023

Locally Adaptive and Differentiable Regression
Mingxuan Han, Varun Shankar, Jeff M Phillips, Chenglong Ye
Convergence Analysis Local Model Local Adaptivity Differentiable Model

June 13, 2023

Neural Mixed Effects for Nonlinear Personalized Predictions
Torsten Wörtwein, Nicholas Allen, Lisa B. Sheeber, Randy P. Auerbach, Jeffrey F. Cohn, Louis-Philippe Morency
Local Model Personalized Prediction

May 18, 2023

AMII: Adaptive Multimodal Inter-personal and Intra-personal Model for Adapted Behavior Synthesis
Jieyeon Woo, Mireille Fares, Catherine Pelachaud, Catherine Achard
Facial Expression Facial Motion Local Model Multimodal Behavior Socially Interactive Agent Behavior Synthesis

March 31, 2023

Models as Agents: Optimizing Multi-Step Predictions of Interactive Local Models in Model-Based Multi-Agent Reinforcement Learning
Zifan Wu, Chao Yu, Chen Chen, Jianye Hao, Hankz Hankui Zhuo
Full Model Multi Agent Multi Agent System Agent Smith Model Based Reinforcement Learning Local Model Step Prediction Model Rollouts Model Based Multi Agent Reinforcement

March 22, 2023

Re-thinking Federated Active Learning based on Inter-class Diversity
SangMook Kim, Sangmin Bae, Hwanjun Song, Se-Young Yun
Active Learning Local Model Selection Policy Class Diversity Federated Active Learning

March 20, 2023

Recursive Euclidean Distance Based Robust Aggregation Technique For Federated Learning
Charuka Herath, Yogachandran Rahulamathavan, Xiaolan Liu
Local Model Robust Aggregation Euclidean Distance Local Update

February 25, 2023

Locale Encoding For Scalable Multilingual Keyword Spotting Models
Pai Zhu, Hyun Jin Park, Alex Park, Angelo Scorza Scarpati, Ignacio Lopez Moreno
Potential Scalability Keyword Spotting Local Model Location Encoding

February 8, 2023

Towards Model-Agnostic Federated Learning over Networks
A. Jung, S. Abdurakhmanova, O. Kuznetsova, Y. SarcheshmehPour
Network Programming Empirical Risk Minimization Heterogeneous Data Local Model Scikit Learn Agnostic Federated Learning

December 6, 2022

Tackling Data Heterogeneity in Federated Learning with Class Prototypes
Yutong Dai, Zeyuan Chen, Junnan Li, Shelby Heinecke, Lichao Sun, Ran Xu
Strong Generalization Class Imbalance Data Heterogeneity Global Model Local Model Class Prototype

December 2, 2022

FedALA: Adaptive Local Aggregation for Personalized Federated Learning
Jianqing Zhang, Yang Hua, Hao Wang, Tao Song, Zhengui Xue, Ruhui Ma, Haibing Guan
Strong Generalization Federated Learning Personalized Federated Learning Local Model Local Aggregation

December 1, 2022

Vertical Federated Learning: A Structured Literature Review
Afsana Khan, Marijn ten Thij, Anna Wilbik
Machine Learning Model Vertical Federated Learning Decentralized Data Local Model

November 21, 2022

PiRL: Participant-Invariant Representation Learning for Healthcare
Zhaoyang Cao, Han Yu, Huiyuan Yang, Akane Sano
Data Driven Meaningful Representation Healthcare System Invariant Representation Local Model Representation Learning Framework