Federated Prompt Cooperation

Federated prompt cooperation explores collaborative machine learning across decentralized datasets, aiming to train shared models while preserving data privacy and addressing data heterogeneity. Current research focuses on adapting various model architectures, including variational autoencoders, transformers, and reinforcement learning algorithms, to this federated setting, often employing techniques like low-rank adaptation and prompt engineering to manage communication overhead and improve model personalization. This approach holds significant promise for applications requiring distributed data analysis, such as healthcare, industrial IoT, and social network analysis, by enabling the development of more accurate and robust models while respecting data privacy constraints.

Papers

February 20, 2023

FederatedTrust: A Solution for Trustworthy Federated Learning
Pedro Miguel Sánchez Sánchez, Alberto Huertas Celdrán, Ning Xie, Gérôme Bovet, Gregorio Martínez Pérez, Burkhard Stiller
Federated Learning Solution Path Federated Prompt Cooperation Federated Setting Trustworthy Machine Learning Comprehensive Trustworthiness

February 5, 2023

Federated Privacy-preserving Collaborative Filtering for On-Device Next App Prediction
Albert Sayapin, Gleb Balitskiy, Daniel Bershatsky, Aleksandr Katrutsa, Evgeny Frolov, Alexey Frolov, Ivan Oseledets, Vitaliy Kharin
Sequential Recommendation Federated Prompt Cooperation Collaborative Filtering Mobile User App Usage Prediction

January 26, 2023

Privacy-Preserving Joint Edge Association and Power Optimization for the Internet of Vehicles via Federated Multi-Agent Reinforcement Learning
Yan Lin, Jinming Bao, Yijin Zhang, Jun Li, Feng Shu, Lajos Hanzo
Multi Agent Reinforcement Learning Federated Prompt Cooperation Vehicle Plan Trade Offs Joint Feature Power Optimization Higher Privacy Level Edge Association

January 17, 2023

Surgical Aggregation: Federated Class-Heterogeneous Learning
Pranav Kulkarni, Adway Kanhere, Paul H. Yi, Vishwa S. Parekh
Deep Learning Model Federated Prompt Cooperation Chest X Ray Datasets Heterogeneous Learning Consistent Aggregation Heterogeneous Training

January 12, 2023

Federated Transfer-Ordered-Personalized Learning for Driver Monitoring Application
Liangqi Yuan, Lu Su, Ziran Wang
LeArning Abstract Internet of Thing Federated Prompt Cooperation Driver Monitoring

January 4, 2023

Privacy and Efficiency of Communications in Federated Split Learning
Zongshun Zhang, Andrea Pinto, Valeria Turina, Flavio Esposito, Ibrahim Matta
High Efficiency Privacy Policy Timely Communication Federated Prompt Cooperation Split Learning Federated Split Learning Privacy Inference

December 29, 2022

Federated Multi-Agent Deep Reinforcement Learning Approach via Physics-Informed Reward for Multi-Microgrid Energy Management
Yuanzheng Li, Shangyang He, Yang Li, Yang Shi, Zhigang Zeng
Energy Consumption Federated Prompt Cooperation DC Microgrid Application Energy Data Physic Based Reward

December 12, 2022

Federated Few-Shot Learning for Mobile NLP
Dongqi Cai, Shangguang Wang, Yaozong Wu, Felix Xiaozhu Lin, Mengwei Xu
LeArning Abstract Natural Language Processing Federated Prompt Cooperation

December 5, 2022

FeSAC: Federated Learning-Based Soft Actor-Critic Traffic Offloading in Space-Air-Ground Integrated Network
Fengxiao Tang, Yilin Yang, Xin Yao, Ming Zhao, Nei Kato
Federated Prompt Cooperation Satellite Network Space Air Ground Integrated Network Soft Actor Critic Algorithm

December 2, 2022

On the Energy and Communication Efficiency Tradeoffs in Federated and Multi-Task Learning
Stefano Savazzi, Vittorio Rampa, Sanaz Kianoush, Mehdi Bennis
Multi Task Learning Federated Prompt Cooperation Energy Policy Research Multi Task Reinforcement Learning Model Agnostic Meta Learning Computation Communication

November 27, 2022

Navigation as Attackers Wish? Towards Building Robust Embodied Agents under Federated Learning
Yunchao Zhang, Zonglin Di, Kaiwen Zhou, Cihang Xie, Xin Eric Wang
Local Navigation Federated Prompt Cooperation Vision and Language Navigation Byzantine Robust State of the Art Defense Pseudo Victim AttackER Agent Learning

November 25, 2022

FedGS: Federated Graph-based Sampling with Arbitrary Client Availability
Zheng Wang, Xiaoliang Fan, Jianzhong Qi, Haibing Jin, Peizhen Yang, Siqi Shen, Cheng Wang
Federated Prompt Cooperation Unbiased Learning Client Sampling Client Availability Graph Sampling

November 21, 2022

SPIN: Simulated Poisoning and Inversion Network for Federated Learning-Based 6G Vehicular Networks
Sunder Ali Khowaja, Parus Khuwaja, Kapal Dev, Angelos Antonopoulos
Generative Adversarial Network Federated Prompt Cooperation Vehicular Network Vehicular Communication

November 20, 2022

Federated deep transfer learning for EEG decoding using multiple BCI tasks
Xiaoxi Wei, A. Aldo Faisal
Federated Prompt Cooperation Deep Transfer Federated Transfer Learning

October 29, 2022

Federated clustering with GAN-based data synthesis
Jie Yan, Jing Liu, Ji Qi, Zhong-Yuan Zhang
Federated Prompt Cooperation Federated Clustering Global Similarity Clustering Framework

October 19, 2022

Latency Aware Semi-synchronous Client Selection and Model Aggregation for Wireless Federated Learning
Liangkun Yu, Xiang Sun, Rana Albelaihi, Chen Yi
Federated Learning Federated Prompt Cooperation Model Aggregation Collaborative Machine Learning Faster Convergence Speed

October 12, 2022

Federated Continual Learning for Text Classification via Selective Inter-client Transfer
Yatin Chaudhary, Pranav Rai, Matthias Schubert, Hinrich Schütze, Pankaj Gupta
Continual LEArning Text Classification Federated Prompt Cooperation Text Classification Task Federated Continual Learning

September 24, 2022

Communication-Efficient {Federated} Learning Using Censored Heavy Ball Descent
Yicheng Chen, Rick S. Blum, Brian M. Sadler
LeArning Abstract Potential Scalability Federated Prompt Cooperation Communication Efficiency Computation Offloading Linear Convergence Rate

September 8, 2022

Federated Prompt Cooperation

Papers

FederatedTrust: A Solution for Trustworthy Federated Learning

Federated Privacy-preserving Collaborative Filtering for On-Device Next App Prediction

Privacy-Preserving Joint Edge Association and Power Optimization for the Internet of Vehicles via Federated Multi-Agent Reinforcement Learning

Surgical Aggregation: Federated Class-Heterogeneous Learning

Federated Transfer-Ordered-Personalized Learning for Driver Monitoring Application

Privacy and Efficiency of Communications in Federated Split Learning

Federated Multi-Agent Deep Reinforcement Learning Approach via Physics-Informed Reward for Multi-Microgrid Energy Management

Federated Few-Shot Learning for Mobile NLP

FeSAC: Federated Learning-Based Soft Actor-Critic Traffic Offloading in Space-Air-Ground Integrated Network

On the Energy and Communication Efficiency Tradeoffs in Federated and Multi-Task Learning

Navigation as Attackers Wish? Towards Building Robust Embodied Agents under Federated Learning

FedGS: Federated Graph-based Sampling with Arbitrary Client Availability

SPIN: Simulated Poisoning and Inversion Network for Federated Learning-Based 6G Vehicular Networks

Federated deep transfer learning for EEG decoding using multiple BCI tasks

Federated clustering with GAN-based data synthesis

Latency Aware Semi-synchronous Client Selection and Model Aggregation for Wireless Federated Learning

Federated Continual Learning for Text Classification via Selective Inter-client Transfer

Communication-Efficient {Federated} Learning Using Censored Heavy Ball Descent

FedDAR: Federated Domain-Aware Representation Learning

FADE: Enabling Federated Adversarial Training on Heterogeneous Resource-Constrained Edge Devices