Results 51 to 60 of about 7,724,255 (252)

White Matter and Perivascular Imaging Changes in Alzheimer's Disease and Cerebral Amyloid Angiopathy

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective Peak‐width of skeletonized mean diffusivity (PSMD) and diffusion tensor imaging–analysis along the perivascular space (DTI‐ALPS), reflecting white matter integrity and glymphatic function, are altered in Alzheimer's disease (AD).
Debina Laishram, Guangwei Du, Sangam Kanekar, Nandakumar Nagaraja   +3 more
wiley   +1 more source

Early Clinical and Cerebrospinal Fluid Predictors of 1‐Year Recurrence in Autoimmune GFAP Astrocytopathy

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective Autoimmune glial fibrillary acidic protein astrocytopathy (GFAP‐A) is an inflammatory central nervous system disorder with variable outcomes. Relapse occurs in a subset of patients, but early predictors remain unclear. We aimed to identify admission‐available features associated with 1‐year recurrence and develop an interpretable ...
Qingting Hong, Yuping Xiao, Yuhan Wu, Ziyuan Huang, Weishan Liang, Li Xiao, Yaqing Shu, Tingting Lu, Yanyu Chang, Wei Qiu, Yuge Wang   +10 more
wiley   +1 more source

Speedy Q-learning [PDF]

, 2011
International audienceWe introduce a new convergent variant of Q-learning, called speedy Q-learning, to address the problem of slow convergence in the standard form of the Q-learning algorithm.
Kappen, Hilbert, Munos, Rémi, Azar, Mohammad Gheshlaghi, Ghavamzadeh, Mohammad   +3 more
core   +2 more sources

Extending Service Beyond Active Duty: Generalizability of Rheumatoid Arthritis Research Conducted Among U.S. Veterans

Arthritis Care &Research, Accepted Article.
Biomedical research involving United States Veterans continues to advance healthcare beyond the Veterans Health Administration. This is particularly true in rheumatoid arthritis (RA), where Veteran‐centric research has uncovered novel insights into pathogenesis, risk factors, and disease manifestations, informing clinical care and research across both ...
Austin M. Wheeler, Joshua F. Baker, Jennifer L. Barton, Maria I. Danila, Tate M. Johnson, Kamini Kuchinad, Kaleb Michaud, Amir A. Razmjou, J. Steuart Richards, Namrata Singh, Isaac D. Smith, Katherine D. Wysham, Grant W. Cannon, Bryant R. England, Amy Joseph, Deana Lazaro, Katherine P. Liao, Courtney Loecker, Andreas Reimold, Beth I. Wallace, Ted R. Mikuls   +20 more
wiley   +1 more source

A Q‐Learning Algorithm to Solve the Two‐Player Zero‐Sum Game Problem for Nonlinear Systems

International Journal of Adaptive Control and Signal Processing, Volume 39, Issue 3, Page 566-581, March 2025.
A Q‐learning algorithm to solve the two‐player zero‐sum game problem for nonlinear systems. ABSTRACT This paper deals with the two‐player zero‐sum game problem, which is a bounded L2$$ {L}_2 $$‐gain robust control problem. Finding an analytical solution to the complex Hamilton‐Jacobi‐Issacs (HJI) equation is a challenging task.
Afreen Islam, Anthony Siming Chen, Guido Herrmann   +2 more
wiley   +1 more source

An optimal dispatch strategy for distributed PV clusters based on Q-learning and pinning consensus algorithm

Zhejiang dianli
To address voltage violations in distribution networks caused by the intermittency and uncertainty of distributed photovoltaic （PV） generation， this paper proposes an optimal cluster dispatch strategy integrating Q-learning and pinning consensus ...
GONG Diyang, TANG Yajie, GAO Weiju, WANG Xiangjin, JIANG Guodong, FU Ming   +5 more
doaj   +1 more source

dynoGP: Deep Gaussian Processes for Dynamic System Identification

International Journal of Adaptive Control and Signal Processing, EarlyView.
This work introduces a novel class of deep models for system identification, dynamical deep Gaussian processes, which combine the strengths of data‐driven methods, such as those based on neural network architectures, with the ability to output a probability distribution for uncertainty representation.
Alessio Benavoli, Marco Forgione, Dario Piga, Marco Zaffalon   +3 more
wiley   +1 more source

Route Optimization for Unmanned Delivery Vehicles Using Improved Q-Learning and Lego-Loma

Journal of Engineering, Project, and Production Management
With the development of technology and economy, unmanned delivery vehicles are being applied across multiple industries. To more accurately design optimal delivery routes and reduce time and energy consumption, this paper builds a route optimization ...
Haohao Yue
doaj   +1 more source

Multi-view positive and unlabeled learning [PDF]

, 2012
Learning with Positive and Unlabeled instances (PU learning) arises widely in information retrieval applications. To address the unavailability issue of negative instances, most existing PU learning approaches require to either identify a reliable set of
Tsang, IW, Mao, Qi, Zhou, JT, Pan, SJ, Pan, Sinno Jialin, Tsang, Ivor W., Zhou, Joey Tianyi, Mao, Q   +7 more
core  

Neural Q-learning for solving PDEs [PDF]

, 2023
Solving high-dimensional partial differential equations (PDEs) is a major challenge in scientific computing. We develop a new numerical method for solving elliptic-type PDEs by adapting the Q-learning algorithm in reinforcement learning.
Cohen, Samuel, Jiang, Deqing, Sirignano, Justin   +2 more
core