2 citations · 8 across the 23 of their papers we have counts for
6 papers · 1 filter
Real-Time Personalized Content Adaptation through Matrix Factorization and Context-Aware Federated Learning
Sai Puppala, Ismail Hossain, Md Jahangir Alam +1
Our study presents a multifaceted approach to enhancing user interaction and content relevance in social media platforms through a federated learning framework. We introduce person…
LLM-Guided Dynamic-UMAP for Personalized Federated Graph Learning
Sai Puppala, Ismail Hossain, Md Jahangir Alam +2
We propose a method that uses large language models to assist graph machine learning under personalization and privacy constraints. The approach combines data augmentation for spar…
Variational Gaussian Mixture Manifold Models for Client-Specific Federated Personalization
Sai Puppala, Ismail Hossain, Md Jahangir Alam +1
Personalized federated learning (PFL) often fails under label skew and non-stationarity because a single global parameterization ignores client-specific geometry. We introduce VGM$…
SocFedGPT: Federated GPT-based Adaptive Content Filtering System Leveraging User Interactions in Social Networks
Sai Puppala, Ismail Hossain, Md Jahangir Alam +1
Our study presents a multifaceted approach to enhancing user interaction and content relevance in social media platforms through a federated learning framework. We introduce person…
FLASH: Federated Learning-Based LLMs for Advanced Query Processing in Social Networks through RAG
Sai Puppala, Ismail Hossain, Md Jahangir Alam +1
Our paper introduces a novel approach to social network information retrieval and user engagement through a personalized chatbot system empowered by Federated Learning GPT. The sys…
Generative AI like ChatGPT in Blockchain Federated Learning: use cases, opportunities and future
Sai Puppala, Ismail Hossain, Md Jahangir Alam +5
Federated learning has become a significant approach for training machine learning models using decentralized data without necessitating the sharing of this data. Recently, the inc…