{"id":20019,"date":"2025-01-09T11:09:22","date_gmt":"2025-01-09T11:09:22","guid":{"rendered":"https:\/\/dataforpublicgood.org.in\/?p=20019"},"modified":"2025-06-27T11:36:54","modified_gmt":"2025-06-27T11:36:54","slug":"minimizing-layerwise-activation-norm-improves-generalization-in-federated-learning","status":"publish","type":"post","link":"https:\/\/dataforpublicgood.org.in\/cdpg\/data-privacy\/minimizing-layerwise-activation-norm-improves-generalization-in-federated-learning\/","title":{"rendered":"Minimizing Layerwise Activation Norm Improves Generalization in Federated Learning"},"content":{"rendered":"\t\t<div data-elementor-type=\"wp-post\" data-elementor-id=\"20019\" class=\"elementor elementor-20019\">\n\t\t\t\t\t\t<div class=\"elementor-inner\">\n\t\t\t\t<div class=\"elementor-section-wrap\">\n\t\t\t\t\t\t\t\t\t<section class=\"elementor-section elementor-top-section elementor-element elementor-element-2dac990 elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"2dac990\" data-element_type=\"section\">\n\t\t\t\t\t\t<div class=\"elementor-container elementor-column-gap-default\">\n\t\t\t\t\t\t\t<div class=\"elementor-row\">\n\t\t\t\t\t<div class=\"elementor-column elementor-col-50 elementor-top-column elementor-element elementor-element-51804ec\" data-id=\"51804ec\" data-element_type=\"column\">\n\t\t\t<div class=\"elementor-column-wrap elementor-element-populated\">\n\t\t\t\t\t\t\t<div class=\"elementor-widget-wrap\">\n\t\t\t\t\t\t<div class=\"elementor-element elementor-element-5ac4424 elementor-widget elementor-widget-text-editor\" data-id=\"5ac4424\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t<div class=\"elementor-text-editor elementor-clearfix\">\n\t\t\t\t<p><em>April 2024<\/em><\/p>\t\t\t\t\t<\/div>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-438085c elementor-widget elementor-widget-text-editor\" data-id=\"438085c\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t<div class=\"elementor-text-editor elementor-clearfix\">\n\t\t\t\t<h1>Minimizing Layerwise Activation Norm Improves Generalization in Federated Learning<\/h1>\t\t\t\t\t<\/div>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-ff9263c elementor-widget elementor-widget-text-editor\" data-id=\"ff9263c\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t<div class=\"elementor-text-editor elementor-clearfix\">\n\t\t\t\t<p style=\"color: blue;\"><strong>Authors<\/strong>: M. Yashwanth, G. K. Nayak, H. Rangwani, A. Singh, R. V. Babu,\u00a0A. Chakraborty<\/p>\t\t\t\t\t<\/div>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-9514863 elementor-widget elementor-widget-text-editor\" data-id=\"9514863\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t<div class=\"elementor-text-editor elementor-clearfix\">\n\t\t\t\t<p>Federated Learning (FL) is an emerging machine learning framework that enables multiple clients (coordinated by a server) to collaboratively train a global model by aggregating the locally trained models without sharing any client&#8217;s training data. It has been observed in recent works that learning in a federated manner may lead the aggregated global model to converge to a &#8216;sharp minimum&#8217; thereby adversely affecting the generalizability of this FL-trained model. Therefore, in this work, we aim to improve the generalization performance of models trained in a federated setup by introducing a &#8216;flatness&#8217; constrained FL optimization problem. This flatness constraint is imposed on the top eigenvalue of the Hessian computed from the training loss. %of the global model. As each client trains a model on its local data, we further re-formulate this complex problem utilizing the client loss functions and propose a new computationally efficient regularization technique, dubbed &#8216;MAN&#8217; which Minimizes Activation&#8217;s Norm of each layer on client-side models. We also theoretically show that minimizing the activation norm reduces the top eigenvalue of the layer-wise Hessian of the client&#8217;s loss, which in turn decreases the overall Hessian&#8217;s top eigenvalue, ensuring convergence to a flat minimum. We apply our proposed flatness-constrained optimization to the existing FL techniques and obtain significant improvements, thereby establishing new state-of-the-art.<\/p>\t\t\t\t\t<\/div>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-85f0dee elementor-widget elementor-widget-text-editor\" data-id=\"85f0dee\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t<div class=\"elementor-text-editor elementor-clearfix\">\n\t\t\t\t<p><strong>Journal\/Conference<\/strong><\/p><p>Winter Conference on Applications of Computer Vision (WACV), 2024<\/p>\t\t\t\t\t<\/div>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t<div class=\"elementor-column elementor-col-50 elementor-top-column elementor-element elementor-element-979fd33\" data-id=\"979fd33\" data-element_type=\"column\">\n\t\t\t<div class=\"elementor-column-wrap elementor-element-populated\">\n\t\t\t\t\t\t\t<div class=\"elementor-widget-wrap\">\n\t\t\t\t\t\t<div class=\"elementor-element elementor-element-4ce5c30 elementor-widget elementor-widget-image\" data-id=\"4ce5c30\" data-element_type=\"widget\" data-widget_type=\"image.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t<div class=\"elementor-image\">\n\t\t\t\t\t\t\t\t\t\t\t\t<img loading=\"lazy\" decoding=\"async\" width=\"400\" height=\"300\" src=\"https:\/\/dataforpublicgood.org.in\/cdpg\/wp-content\/uploads\/2025\/01\/Minimizing-Layerwise-Activation-Norm-Improves-Generalization-in-Federated-Learning.jpg\" class=\"attachment-full size-full\" alt=\"\" \/>\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-c27cce3 elementor-button-success elementor-align-center elementor-widget elementor-widget-button\" data-id=\"c27cce3\" data-element_type=\"widget\" data-widget_type=\"button.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<div class=\"elementor-button-wrapper\">\n\t\t\t<a href=\"https:\/\/ieeexplore.ieee.org\/document\/10484492\" target=\"_blank\" class=\"elementor-button-link elementor-button elementor-size-sm elementor-animation-shrink\" role=\"button\">\n\t\t\t\t\t\t<span class=\"elementor-button-content-wrapper\">\n\t\t\t\t\t\t<span class=\"elementor-button-text\">Know more<\/span>\n\t\t<\/span>\n\t\t\t\t\t<\/a>\n\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<section class=\"elementor-section elementor-top-section elementor-element elementor-element-3d308ba elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"3d308ba\" data-element_type=\"section\">\n\t\t\t\t\t\t<div class=\"elementor-container elementor-column-gap-default\">\n\t\t\t\t\t\t\t<div class=\"elementor-row\">\n\t\t\t\t\t<div class=\"elementor-column elementor-col-100 elementor-top-column elementor-element elementor-element-e1458bc\" data-id=\"e1458bc\" data-element_type=\"column\">\n\t\t\t<div class=\"elementor-column-wrap elementor-element-populated\">\n\t\t\t\t\t\t\t<div class=\"elementor-widget-wrap\">\n\t\t\t\t\t\t<div class=\"elementor-element elementor-element-5229c9c elementor-widget elementor-widget-html\" data-id=\"5229c9c\" data-element_type=\"widget\" data-widget_type=\"html.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t<style>\n    .post-style-3 .entry-header {\n        display: none;\n    }\n    \n    h1 {\n        font-size:28px !important;\n        text-transform: inherit !important;\n    }\n    \n<\/style>\n\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<div style=\"margin-top: 0px; margin-bottom: 0px;\" class=\"sharethis-inline-share-buttons\" ><\/div>","protected":false},"excerpt":{"rendered":"<p>April 2024 Minimizing Layerwise Activation Norm Improves Generalization in Federated Learning Authors: M. Yashwanth, G. K. Nayak, H. Rangwani, A. Singh, R. V. Babu,\u00a0A. Chakraborty Federated Learning (FL) is an emerging machine learning framework that enables multiple clients (coordinated by a server) to collaboratively train a global model by aggregating the locally trained models without sharing any client&#8217;s training data. &hellip;<\/p>\n","protected":false},"author":2,"featured_media":20137,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":"","_links_to":"","_links_to_target":""},"categories":[92],"tags":[],"class_list":["post-20019","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-data-privacy"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v20.12 - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>Minimizing Layerwise Activation Norm Improves Generalization in Federated Learning - Data for Public Good<\/title>\n<meta name=\"description\" content=\"Federated Learning (FL) is an emerging machine learning framework that enables multiple clients (coordinated by a server) to collaboratively train a global model by aggregating the locally trained models without sharing any client\u2019s training data.\" \/>\n<meta name=\"robots\" content=\"noindex, nofollow\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Minimizing Layerwise Activation Norm Improves Generalization in Federated Learning - 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