Federated Learning

A Research Group from Stanford Studied the Possible Fine-Tuning Techniques to Generalize Latent Diffusion Models for Medical Imaging Domains

AI Paper SummaryMarch 30, 2023

Latent diffusion models have greatly increased in popularity in recent years. Because their outstanding generating capabilities, these models can produce high-fidelity synthetic datasets that can be added to supervised machine learning pipelines in situations when training...

Cerebras Releases 7 GPT-based Large Language Models for Generative AI

AI ShortsMarch 30, 2023

Rising entry barriers are hindering AI's potential to revolutionize global trade. OpenAI's GPT4 is the most recent big language model to be disclosed. However, the model's architecture, training data, hardware, and hyperparameters are kept secret. Large...

IOM Releases Its Second Synthetic Dataset From Trafficking Victim Case Records Generated With Differential Privacy And AI From Microsoft

AI ShortsDecember 11, 2022

Researchers at Microsoft are committed to researching ways technology may help the world's most marginalized peoples improve their human rights situations. Their expertise spans...

This Artificial Intelligence Paper Presents an Advanced Method for Differential Privacy in Image Recognition with Better Accuracy

AI Paper SummaryNovember 30, 2022

Machine learning has increased considerably in several areas due to its performance in recent years. Thanks to modern computers' computing capacity and graphics cards,...

Researchers Developed SmoothNets For Optimizing Convolutional Neural Network (CNN) Architecture Design For Differentially Private Deep Learning

AI Paper SummarySeptember 30, 2022

Differential privacy (DP) is used in machine learning to preserve the confidentiality of the information that forms the dataset. The most used algorithm to...

Researchers Analyze the Current Findings on Confidential Computing-Assisted Machine Learning ML Security and Privacy Techniques Along with the Limitations in Existing Trusted Execution Environment...

AI Paper SummarySeptember 10, 2022

The evolution of machine learning (ML) offers broader possibilities of use. However, wide applications also increase the risks of large attack surface on ML's...

3 Machine Learning Business Challenges Rooted in Data Sensitivity

AI GovernanceSeptember 8, 2022

Machine Learning (ML) and, in particular, Deep Learning is drastically changing the way we conduct business as now data can be utilized to guide...

Researchers created a Novel Framework called ‘FedD3’ for Federated Learning in Resource-Constrained Edge Environments via Decentralized Dataset Distillation

AI Paper SummarySeptember 4, 2022

For collaborative learning in large-scale distributed systems with a sizable number of networked clients, such as smartphones, connected cars, or edge devices, federated learning...

University of Michigan Researchers Open-Source ‘FedScale’: a Federated Learning (FL) Benchmarking Suite with Realistic Datasets and a Scalable Runtime to Enable Reproducible FL Research...

AI Paper SummaryJuly 23, 2022

Federated learning (FL) is a new machine learning (ML) environment in which a logically centralized coordinator orchestrates numerous dispersed clients (e.g., cellphones or laptops)...

Researchers At Amazon Propose ‘AdaMix’, An Adaptive Differentially Private Algorithm For Training Deep Neural Network Classifiers Using Both Private And Public Image Data

AI Paper SummaryJune 26, 2022

It is crucial to preserve privacy by restricting the amount of data that may be gathered about each training sample when training a deep...

Stanford AI Researchers Propose ‘FOCUS’: A Foundation Model Which Aims to Achieve Perfect Secrecy For Personal Tasks

AI Paper SummaryJune 17, 2022

Machine learning holds the possibility of assisting people with personal activities. Personal jobs range from well-known activities like subject categorization over personal correspondence and...

Researchers From China Introduce ‘FedPerGNN’: A New Federated Graph Neural Network (GNN) Framework For Both Effective And Privacy-Preserving Personalization

AI EthicsJune 11, 2022

This Article is written as a summay by Marktechpost Staff based on the paper 'A federated graph neural network framework for privacy-preserving personalization'. All...

Borealis AI Research Introduces fAux: A New Approach To Test Individual Fairness via Gradient Alignment

AI ShortsMay 28, 2022

Machine learning models are trained on massive datasets with hundreds of thousands, if not billions, of parameters. However, how these models translate the input...