{"id":662,"date":"2021-05-03T15:01:25","date_gmt":"2021-05-03T13:01:25","guid":{"rendered":"https:\/\/portale.unime.it\/modellopersona\/?page_id=12"},"modified":"2025-04-13T17:30:56","modified_gmt":"2025-04-13T15:30:56","slug":"home","status":"publish","type":"page","link":"https:\/\/portale2.unime.it\/fairground2025\/","title":{"rendered":"HOME"},"content":{"rendered":"\t\t
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artiFicial And bio-inspIred netwoRked \nintelliGence foR\ncOnstrained aUtoNomous Devices
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Pontificia Universit\u00e0 Gregoriana, Rome, Italy <\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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June 30th - July 5th 2025<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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THE WORKSHOP<\/h3>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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On-device training using edge computing allows intelligent devices to learn autonomously while improving latency and security. However, resource constraints remain a challenge. Techniques like weight compression, federated learning, and transfer learning help but may not meet hardware needs. Neuromorphic solutions, such as SNNs, mimic brain-like, energy-efficient, event-driven computation, ideal for robots and implants. They bridge neuroscience and AI, overcoming limitations of traditional ANNs and adapting to dynamic environments. This workshop explores neuromorphic systems and bio-inspired architectures, combined with traditional networks, to optimize computational resources for diverse applications.<\/h5>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t
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PROGRAMME<\/a><\/h4>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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COMMITTEE<\/a><\/h4>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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CALL <\/a><\/h4>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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REGISTRATION<\/a><\/h4>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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artiFicial And bio-inspIred netwoRked intelliGence foR cOnstrained aUtoNomous Devices(FAIRGROUND) Pontificia Universit\u00e0 Gregoriana, Rome, Italy June 30th – July 5th 2025 PROGRAMME REGISTRATION THE WORKSHOP On-device training using edge computing allows intelligent devices to learn autonomously while improving latency and security. However, resource constraints remain a challenge. Techniques like weight compression, federated learning, and transfer learning… Continue reading HOME<\/span><\/a><\/p>\n","protected":false},"author":1,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"elementor_header_footer","meta":{"footnotes":""},"class_list":["post-662","page","type-page","status-publish","hentry","entry"],"yoast_head":"\nHOME - Fairground2025<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/portale2.unime.it\/fairground2025\/\" \/>\n<meta property=\"og:locale\" content=\"en_GB\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"HOME - Fairground2025\" \/>\n<meta property=\"og:description\" content=\"artiFicial And bio-inspIred netwoRked intelliGence foR cOnstrained aUtoNomous Devices(FAIRGROUND) Pontificia Universit\u00e0 Gregoriana, Rome, Italy June 30th – July 5th 2025 PROGRAMME REGISTRATION THE WORKSHOP On-device training using edge computing allows intelligent devices to learn autonomously while improving latency and security. 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