Combinatorial optimization problems are often encountered in real-world applications, including logistics, scheduling and ...
The energy sector is becoming a highly connected cyber-physical ecosystem in which distributed energy resources, electric ...
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Data Scientist Ke Zhang’s Research Explores Homomorphic Encryption for Privacy-Preserving Marketing
A privacy-preserving marketing framework applies homomorphic encryption to perform machine learning on encrypted ...
The premise is straightforward — we are awash in biological data. The rapid growth of multiomics datasets (genomics, transcriptomics, proteomics, metabolomics, and radiomics) together with ...
Atharv Kolhar, a staff test automation engineer at Figure AI, says the robotics industry needs a testing philosophy that ...
ABSTRACT: Bipolar disorder (BD) affects approximately 45 million individuals worldwide and is characterized by recurrent episodes of mania, hypomania, and depression, with an average diagnostic delay ...
Federated Learning (FL) is a distributed Machine Learning (ML) paradigm that enables multiple local devices, that is, clients, and a central server to collaboratively train a ML model using data ...
If it feels like social platforms suddenly “get” you more than they used to, you’re not imagining it! In 2026, feeds aren’t only reacting to what you click anymore. They’re predicting what you ...
This GitHub repository contains the code, data, and figures for the paper FedRAIN-Lite: Federated Reinforcement Algorithms for Improving Idealised Numerical Weather and Climate Models. Also includes ...
Vikram Gupta is Chief Product Officer, SVP & GM of the IoT Processor Business Division at Synaptics, a leading EdgeAI semiconductor company. In my previous articles, I explored how the rapid growth of ...
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