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Personalized Federated Learning With a Graph
Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence, 2022 Knowledge sharing and model personalization are two key components in the conceptual framework of personalized federated learning (PFL). Existing PFL methods focus on proposing new model personalization mechanisms while simply implementing knowledge sharing by aggregating models from all clients, regardless of their relation graph.
Chen, Fengwen +4 more
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A Personalized Learning Service Compatible with Moodle E-Learning Management System
Applied Sciences, 2022 Among the numerous learning management platforms, Moodle is free, open-source software supporting expanding and modularized system functions and services to facilitate online courses or online resources and interactive activities.
Yi-Chun Chang, Jian-Wei Li, De-Yao Huang
doaj +1 more source
PeFLL: Personalized Federated Learning by Learning to Learn
, 2023 We present PeFLL, a new personalized federated learning algorithm that improves over the state-of-the-art in three aspects: 1) it produces more accurate models, especially in the low-data regime, and not only for clients present during its training phase, but also for any that may emerge in the future; 2) it reduces the amount of on-client computation ...
Scott, Jonathan A +2 more
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Unsupervised clothing change adaptive person ReID [PDF]
, 2021 Clothing changes and lack of data labels are both crucial challenges in person ReID. For the former challenge, people may occur multiple times at different locations wearing different clothing. However, most of the current person ReID research works focus on the benchmarks in which a person's clothing is kept the same all the time.
arxiv +1 more source
The Montessori Approach as a Model of Personalized Instruction
Journal of Montessori Research, 2020 I present a brief overview of the key elements of personalized learning and Montessori education, a related pedagogical approach, aiming to examine common theoretical principles and key elements.
Marusa Mavric
doaj +1 more source
Group Privacy for Personalized Federated Learning
Proceedings of the 9th International Conference on Information Systems Security and Privacy, 2023 Federated learning (FL) is a type of collaborative machine learning where participating peers/clients process their data locally, sharing only updates to the collaborative model. This enables to build privacy-aware distributed machine learning models, among others.
Galli, Filippo +4 more
openaire +6 more sources
Learning of personalized security settings [PDF]
2010 IEEE International Conference on Systems, Man and Cybernetics, 2010 While many cybersecurity tools are available to computer users, their default configurations often do not match needs of specific users. Since most modern users are not computer experts, they are often unable to customize these tools, thus getting either insufficient or excessive security.
Jaime G. Carbonell +2 more
openaire +2 more sources
Smart Learning Environments, 2019 Smart devices and intelligent technologies are enabling a smart learning environment to effectively promote the development of personalized learning and adaptive learning, in line with the trend of accelerating the integration of both. In this regard, we
Hongchao Peng +2 more
doaj +1 more source
Learning Implicit User Profiles for Personalized Retrieval-Based Chatbot [PDF]
, 2021 In this paper, we explore the problem of developing personalized chatbots. A personalized chatbot is designed as a digital chatting assistant for a user. The key characteristic of a personalized chatbot is that it should have a consistent personality with the corresponding user.
arxiv +1 more source
Subtask-dominated Transfer Learning for Long-tail Person Search [PDF]
arXiv, 2021 Person search unifies person detection and person re-identification (Re-ID) to locate query persons from the panoramic gallery images. One major challenge comes from the imbalanced long-tail person identity distributions, which prevents the one-step person search model from learning discriminative person features for the final re-identification ...
arxiv