Self Supervised Learning News Today : Breaking News, Live Updates & Top Stories | Vimarsana

Stay updated with breaking news from Self supervised learning. Get real-time updates on events, politics, business, and more. Visit us for reliable news and exclusive interviews.

Top News In Self Supervised Learning Today - Breaking & Trending Today

The Need For AI-Informed Defense: How AI Empowers Security Teams

Ongoing collaboration is crucial for security teams and AI to form a powerful defense against cyber threats by working together. ....

Joe Ariganello , Forbes Communications Council , Product Marketing , Machine Learning , Time Detection , Prediction And Prevention , Self Supervised Learning , False Positives And Negatives , Data Dependency And Bias , Focus On Accuracy , Emphasis On Explainability , Informed Defense , How Security Teams And , Enhanced Threat Detection , Improved Threat Analysis And Prioritization , Security Automation , Communications Council ,

"<italic>FLPurifier</italic>: Backdoor Defense in Federated Learning vi" by Jiale Zhang, Chengcheng Zhu et al.

Recent studies have demonstrated that backdoor attacks can cause a significant security threat to federated learning. Existing defense methods mainly focus on detecting or eliminating the backdoor patterns after the model is backdoored. However, these methods either cause model performance degradation or heavily rely on impractical assumptions, such as labeled clean data, which exhibit limited effectiveness in federated learning. To this end, we propose FLPurifier, a novel backdoor defense method in federated learning that can effectively purify the possible backdoor attributes before federated aggregation. Specifically, FLPurifier splits a complete model into a feature extractor and classifier, in which the extractor is trained in a decoupled contrastive manner to break the strong correlation between trigger features and the target label. Compared with existing backdoor mitigation methods, FLPurifier doesn’t rely on impractical assumptions since it can effectively purify the backdoo ....

Adaptation Models , Daptive Classifier Aggregation , Backdoor Attacks , Ecoupled Contrastive Training , Feature Extraction , Federated Learning , Self Supervised Learning ,

Human Activity Recognition through Self-Supervised Learning

Researchers from the UK demonstrate the efficacy of self-supervised learning for human activity recognition using a vast wearable dataset. By addressing convergence issues and evaluating multi-task self-supervision, they showcase robust models with superior representation quality across diverse populations and activity types. ....

United Kingdom , Noopur Jain , Susha Cheriyedath , Noopur Jainapr , Digital Medicine , Human Activity Recognition , Self Supervised Learning , United Kingdom Biobank ,

A Budding Computer Scientist, Shreyas Fadnavis Making Substantial Contributions in the Field of Medical Imaging

A Budding Computer Scientist, Shreyas Fadnavis Making Substantial Contributions in the Field of Medical Imaging
thehindubusinessline.com - get the latest breaking news, showbiz & celebrity photos, sport news & rumours, viral videos and top stories from thehindubusinessline.com Daily Mail and Mail on Sunday newspapers.

Shreyas Fadnavis , Richard Feynman , Harvard University , Pune Institute Of Computer Technology , University Of Pune , Phd Research Intern , Harvard Medical School , Indiana University Bloomington , Computer Scientist , Finding Things Out , Pune Institute , Computer Technology , Computer Engineering , Data Structures , Natural Language Processing , Artificial Intelligence , Machine Learning , Bayesian Theory , Image Processing , Combinatorial Topology , Self Supervised Learning , Diffusion Imaging , Spotlight Presentation , Neural Information Processing Systems , Multi View Learning , Pulmonary Hypertension ,

The brain may learn about the world the same way some computational models do

New MIT studies support the idea that the brain uses a process similar to a machine-learning approach known as “self-supervised learning.” This type of machine learning allows computational models to learn about visual scenes based solely on the similarities and differences between them, with no labels or other information. ....

Aran Nayebi , Rylan Schaeffer , Ila Fiete , Mehrdad Jazayeri , Robert Yang , Mikail Khona , K Lisa Yang Icon Center , National Institutes Of Health , Helen Hay Whitney Foundation , Mcgovern Institute For Brain Research , Mcgovern Institute , Mcknight Foundation , Icon Center , Simons Foundation , Yang Integrative Computational Neuroscience , Rishi Rajalingham , Meta Reality Labs , Brain Research , Neural Information Processing Systems , National Institutes , Helen Hay Whitney , Self Supervised Learning , Grid Cells , Computational Models , Ila Fiete , Mehrdad Jazayeri ,