Results 41 to 50 of about 1,153,224 (274)
Complexity, 2021 Security issue against different attacks is the core topic of cyberphysical systems (CPSs). In this paper, optimal control theory, reinforcement learning (RL), and neural networks (NNs) are integrated to provide a brief overview of optimal robust control
Bo Hu +5 more
doaj +1 more source
Bagging Provides Assumption-free Stability [PDF]
arXiv, 2023 Bagging is an important technique for stabilizing machine learning models. In this paper, we derive a finite-sample guarantee on the stability of bagging for any model. Our result places no assumptions on the distribution of the data, on the properties of the base algorithm, or on the dimensionality of the covariates.
arxiv
Mental models vs cell schemes [PDF]
Investigações em Ensino de Ciências, 2002 Student's mental representations of cell are examined from the perspectives of Johnson-Laird's mental models theory five years after instruction. The observed identity and stability of such representations are then interpreted under the framework of ...
Mª Luz Rodríguez Palmero +1 more
doaj
Differential Privacy in Federated Learning: An Evolutionary Game Analysis
Applied SciencesThis paper examines federated learning, a decentralized machine learning paradigm, focusing on privacy challenges. We introduce differential privacy mechanisms to protect privacy and quantify their impact on global model performance.
Zhengwei Ni, Qi Zhou
doaj +1 more source
Robust Stability of Neural Network-controlled Nonlinear Systems with Parametric Variability [PDF]
arXiv, 2021 Stability certification and identifying a safe and stabilizing initial set are two important concerns in ensuring operational safety, stability, and robustness of dynamical systems. With the advent of machine-learning tools, these issues need to be addressed for the systems with machine-learned components in the feedback loop.
arxiv
International Journal of Applied Mathematics and Computer Science, 2014 This paper is concerned with the problem of designing a robust modified repetitive-control system with a dynamic output feedback controller for a class of strictly proper plants.
Zhou Lan, She Jinhua, Zhou Shaowu
doaj +1 more source
Stable Modular Control via Contraction Theory for Reinforcement Learning [PDF]
arXiv, 2023 We propose a novel way to integrate control techniques with reinforcement learning (RL) for stability, robustness, and generalization: leveraging contraction theory to realize modularity in neural control, which ensures that combining stable subsystems can automatically preserve the stability.
arxiv
The power of microRNA regulation—insights into immunity and metabolism
FEBS Letters, EarlyView.MicroRNAs are emerging as crucial regulators at the intersection of metabolism and immunity. This review examines how miRNAs coordinate glucose and lipid metabolism while simultaneously modulating T‐cell development and immune responses. Moreover, it highlights how cutting‐edge artificial intelligence applications can identify miRNA biomarkers ...
Stefania Oliveto +2 more
wiley +1 more source
Molecular Oncology, EarlyView.Urine is a rich source of biomarkers for cancer detection. Tumor‐derived material is released into the bloodstream and transported to the urine. Urine can easily be collected from individuals, allowing non‐invasive cancer detection. This review discusses the rationale behind urine‐based cancer detection and its potential for cancer diagnostics ...
Birgit M. M. Wever +1 more
wiley +1 more source
Molecular Oncology, EarlyView.There is an unmet need in metastatic breast cancer patients to monitor therapy response in real time. In this study, we show how a noninvasive and affordable strategy based on sequencing of plasma samples with longitudinal tracking of tumour fraction paired with a statistical model provides valuable information on treatment response in advance of the ...
Emma J. Beddowes +20 more
wiley +1 more source