Results 51 to 60 of about 1,466,211 (327)
Stability and Learning in Strategic Queuing Systems [PDF]
ACM Conference on Economics and Computation, 2020 Bounding the price of anarchy, which quantifies the damage to social welfare due to selfish behavior of the participants, has been an important area of research in algorithmic game theory.
J. Gaitonde, É. Tardos
semanticscholar +1 more source
From synaptic interactions to collective dynamics in random neuronal networks models: critical role of eigenvectors and transient behavior [PDF]
, 2018 The study of neuronal interactions is currently at the center of several neuroscience big collaborative projects (including the Human Connectome, the Blue Brain, the Brainome, etc.) which attempt to obtain a detailed map of the entire brain matrix. Under
Chialvo, Dante R. +4 more
core +2 more sources
Learning and performing: What can theory offer high performance sports practitioners?
Brazilian Journal of Motor Behavior, 2022 Currently, the most prominent motor control theories that underpin the pedagogy of coaches in high performance sport are derived from the discipline of psychology with a dominant focus on internalised control processes for learning and performance.
I. Renshaw, K. Davids, Mark O’Sullivan
semanticscholar +1 more source
Predicting the thermodynamic stability of perovskite oxides using machine learning models
, 2018 Perovskite materials have become ubiquitous in many technologically relevant applications, ranging from catalysts in solid oxide fuel cells to light absorbing layers in solar photovoltaics.
Jacobs, Ryan, Li, Wei, Morgan, Dane
core +1 more source
Sparse and spurious: dictionary learning with noise and outliers [PDF]
, 2015 A popular approach within the signal processing and machine learning communities consists in modelling signals as sparse linear combinations of atoms selected from a learned dictionary.
Bach, Francis +2 more
core +4 more sources
Identifying an efficient, thermally robust inorganic phosphor host via machine learning
Nature Communications, 2018 Identifying phosphors with good thermal stability and quantum efficiency is a prerequisite to improve the performance of white LED light sources. Here, a combined machine learning and density functional theory method is introduced to identify next ...
Ya Zhuo +4 more
doaj +1 more source
Complexity, 2022 This paper proposes an adaptive formation tracking control algorithm optimized by Q-learning scheme for multiple mobile robots. In order to handle the model uncertainties and external disturbances, a desired linear extended state observer is designed to ...
Chen Zhang +4 more
doaj +1 more source
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
From omics to AI—mapping the pathogenic pathways in type 2 diabetes
FEBS Letters, EarlyView.Integrating multi‐omics data with AI‐based modelling (unsupervised and supervised machine learning) identify optimal patient clusters, informing AI‐driven accurate risk stratification. Digital twins simulate individual trajectories in real time, guiding precision medicine by matching patients to targeted therapies.
Siobhán O'Sullivan +2 more
wiley +1 more source
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