The paper “Split Happens” by Tanveer Khan, Mindaugas Budzys and Antonis Michalas examines leakage in split learning and introduces an FSS-based protocol to keep data and labels on the client. 📰harpocrates-project.eu/splithappens-c… #SplitLearning #FunctionSecretSharing #MachineLearning

🔔 Welcome to read Editor's Choice Articles in the Q1 of 2024: 📌Title: Multi-Level Split #FederatedLearning for Large-Scale AIoT System Based on Smart Cities mdpi.com/1999-5903/16/3… #splitlearning #artificialintelligent #internetofthings #edgecomputing @ComSciMath_Mdpi

📢 MDPIfutureinternet [Top Cited Papers in 2024] 🚩Title: Multi-Level Split #FederatedLearning for Large-Scale #AIoT System Based on Smart Cities 📌Views: 3728 📌Citations: 7 🔗mdpi.com/1999-5903/16/3… #splitlearning #artificialintelligent #edgecomputing @ComSciMath_Mdpi

Advancing Edge Deployments: Solutions for Language Models Optimisation 🌐 #ModelQuantization: Reduces model size and computational needs. 🔧 Parameter-Efficient #FineTuning: Optimizes specific parameters for efficiency. 🔀 #SplitLearning: Divides workloads between devices and servers. 🤝 #CollaborativeComputing: Shares inference tasks across systems. ⚡ Energy Optimization: Techniques like #sparsityprediction reduce power consumption.

📢Welcome to read the paper by Praveen Joshi et al. | Performance and Information Leakage in Splitfed Learning and Multi-Head #SplitLearning in #HealthcareData and Beyond 👉mdpi.com/2409-9279/5/4/… #article #machinelearning #datacollection #dataset

In his talk at #BAS22, @michikuehne, Founder and CEO of @Katulu_io, outlines the concepts behind #SplitLearning and how it can be transferred to industrial processes across multiple companies: "With federated learning you can solve key problems - without sharing data."

Found a really nice paper on #splitlearning applied to QoE by my colleagues @selimickin, Konstantinos Vandikas, and Markus Fiedler: mdpi.com/2673-8732/1/2/…

How reliably does #splitlearning safeguard private information? @gg159136 and @vectorinversion in our @LiveRamp privacy tech group published their paper on #splitnn attacks and thwarting them with #differentialprivacy in @RealAAAI Check it out: arxiv.org/abs/2201.04018

Our new preprint - *FedSL*, we propose a novel Federated and #SplitLearning technique for training sequentially distributed data using #RNN, and show its works better than conventional methods on #EHR data. Great Work @abediai #FederatedLearning #CloudAI tinyurl.com/yxfogn8z

Safe Paths: A privacy-first approach to contact tracing @medialab @MIT @MILAMontreal media.mit.edu/projects/safep… #Splitlearning #NeuralNetworks safepaths.mit.edu

Great work being led by @raskarmit @johnkwerner on possible way of using #splitlearning for #covid_19 tracking

and some of the ongoing MIT projects was really informative and enlightening. Hearing him talk about split learning and federated learning really did open our thinking horizons! (2) #REDX #splitlearning #federatedlearning #innovation #machinelearning #deeplearning #makermela

Listen to @proneat from @MIT talk about #SplitLearning: A Resource Efficient Distributed #DeepLearning Method without Sensitive Data Sharing bit.ly/2Le3239

AI on Siloed Data: Sharing wisdom not raw data. Beyond anonymization to protect data, towards #datautility. Specific reference to applications in legal. #ImaginationInAction splitlearning.github.io #Splitlearning #datacommons @jamesondempsey

Great idea to use #splitlearning & #federatedlearning to enable #ML at a large scale while protecting individual data privacy. Huge implications for #healthcare #imaginationinaction @raskarmit

.@proneat from @MIT talked about #SplitLearning, a recently developed, highly resource efficient method for collaboration in the health sector, allowing to perform distributed deep learning under data sharing constraints. Download slides bit.ly/2VRy9Uu #datacouncil

Data Council SF '19 Speaker Announcement: @proneat from @MIT will talk about "#SplitLearning: A Resource Efficient Distributed #DeepLearning Method without Sensitive Data Sharing". Book your tickets now bit.ly/2UdhGx5 #datacouncil

Split learning is a new technique to approach machine learning from sensitive data (that can not be consolidated). Split learning leaves the data in place & uses it arxiv.org/pdf/1812.00564… #AI #Splitlearning