Results 41 to 50 of about 91,570 (234)

Federated Learning Via Inexact ADMM

IEEE Transactions on Pattern Analysis and Machine Intelligence, 2023
One of the crucial issues in federated learning is how to develop efficient optimization algorithms. Most of the current ones require full device participation and/or impose strong assumptions for convergence. Different from the widely-used gradient descent-based algorithms, in this paper, we develop an inexact alternating direction method of ...
Shenglong Zhou, Geoffrey Ye Li
openaire   +4 more sources

Multi-Objective Evolutionary Federated Learning [PDF]

IEEE Transactions on Neural Networks and Learning Systems, 2020
Federated learning is an emerging technique used to prevent the leakage of private information. Unlike centralized learning that needs to collect data from users and store them collectively on a cloud server, federated learning makes it possible to learn a global model while the data are distributed on the users' devices.
Zhu, Hangyu, Jin, Yaochu
openaire   +4 more sources

Deep Learning–Assisted Differentiation of Four Peripheral Neuropathies Using Corneal Confocal Microscopy

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective Peripheral neuropathies contribute to patient disability but may be diagnosed late or missed altogether due to late referral, limitation of current diagnostic methods and lack of specialized testing facilities. To address this clinical gap, we developed NeuropathAI, an interpretable deep learning–based multiclass classification ...
Chaima Ben Rabah, Ioannis N. Petropoulos, Mark Stettner, Maryam Ferdousi, Uazman Alam, Nathan Efron, Ahmed Serag, Rayaz A. Malik   +7 more
wiley   +1 more source

In Materia Shaping of Randomness with a Standard Complementary Metal‐Oxide‐Semiconductor Transistor for Task‐Adaptive Entropy Generation

Advanced Functional Materials, EarlyView.
This study establishes a materials‐driven framework for entropy generation within standard CMOS technology. By electrically rebalancing gate‐oxide traps and Si‐channel defects in foundry‐fabricated FDSOI transistors, the work realizes in‐materia control of temporal correlation – achieving task adaptive entropy optimization for reinforcement learning ...
Been Kwak, Ryun‐Han Koo, Youngchan Cho, Changhyeon Han, Dongbin Kim, Soi Jeong, Yunho Shin, Joonhyeok Choi, Jiseong Im, Jonghyun Ko, Jong‐Ho Lee, Jangsaeng Kim, Youngho Kang, Wonjun Shin, Daewoong Kwon   +14 more
wiley   +1 more source

Benchmark for Personalized Federated Learning

IEEE Open Journal of the Computer Society
Federated learning is a distributed machine learning approach that allows a single server to collaboratively build machine learning models with multiple clients without sharing datasets.
Koji Matsuda, Yuya Sasaki, Chuan Xiao, Makoto Onizuka   +3 more
doaj   +1 more source

Advancements of Federated Learning Towards Privacy Preservation: From Federated Learning to Split Learning [PDF]

, 2021
Authors' preprint version (before any peer-review) of a book chapter to appear in the Book series "Studies in Computational Intelligence", Book title "Federated Learning Systems: Towards Next-generation AI", Book eds. Muhammad Habib ur Rehman and Mohamed Medhat Gaber, Publisher "Springer Nature Switzerland AG Gewerbestrasse 11, 6330 Cham, Switzerland."
Thapa, Chandra, Chamikara, M. A. P., Camtepe, Seyit A.   +2 more
openaire   +2 more sources

Smart Catheters for Diagnosis, Monitoring, and Therapy

Advanced Healthcare Materials, EarlyView.
This study presents a comprehensive review of smart catheters, an emerging class of medical devices that integrate embedded sensors, robotics, and communication systems, offering increased functionality and complexity to enable real‐time health monitoring, diagnostics, and treatment. Abstract This review explores smart catheters as an emerging class of
Azra Yaprak Tarman, Samiha Ahmed, Majed Othman Althumayri, Megan Guy, Darlenne Chavez Lugo, Frances S. Ligler, George T. Ligler, Rahmi Oklu, Hiroshi Kawahira, Michael J. McShane, Jun Kameoka, Jonathan Bova, Hatice Ceylan Koydemir   +12 more
wiley   +1 more source

Learning domain-heterogeneous speaker recognition systems with personalized continual federated learning

EURASIP Journal on Audio, Speech, and Music Processing, 2023
Speaker recognition, the process of automatically identifying a speaker based on individual characteristics in speech signals, presents significant challenges when addressing heterogeneous-domain conditions.
Zhiyong Chen, Shugong Xu
doaj   +1 more source

Beyond Presumptions: Toward Mechanistic Clarity in Metal‐Free Carbon Catalysts for Electrochemical H2O2 Production via Data Science

Advanced Materials, EarlyView.
Metal‐free carbon catalysts enable the sustainable synthesis of hydrogen peroxide via two‐electron oxygen reduction; however, active site complexity continues to hinder reliable interpretation. This review critiques correlation‐based approaches and highlights the importance of orthogonal experimental designs, standardized catalyst passports ...
Dayu Zhu, Hsi‐wen Wu, Xiao Wang, Jie Zhang   +3 more
wiley   +1 more source

The GLASS project: supporting secure shibboleth-based single sign-on to campus resources [PDF]

, 2007
Higher and Further education institutions in the UK are in the process of migrating their IT infrastructures to exploit Shibboleth technologies for federated access management. Ease of use and secure access are paramount to the successful uptake of these
Jiang, J., Sinnott, R.O., Watt, J.
core   +2 more sources