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Efficient Learning Machines: Theories, Concepts, and Applications for Engineers and System Designers
Machine learning techniques provide cost-effective alternatives to traditional methods for extracting underlying relationships between information and data and for predicting future events by processing existing information ...
Optimal transport for machine learning: theory and applications
(2021-03-25)
O que os operadores de produção de petróleo valorizam ao comprar produtos químicos?: uma análise sobre a percepção de valor na decisão de compra ou contratação de um provedor de especialidades químicas no mercado de óleo ...
Learning Reward Machines: A Study in Partially Observable Reinforcement Learning
(2023)
Reinforcement Learning (RL) is a machine learning paradigm wherein an artificial agentinteracts with an environment with the purpose of learning behaviour that maximizesthe expected cumulative reward it receives from the ...
Efficient Reinforcement Learning using Gaussian Processes
This book examines Gaussian processes in both model-based reinforcement learning (RL) and inference in nonlinear dynamic systems.First, we introduce PILCO, a fully Bayesian approach for efficient RL in continuous-valued ...
Harnessing machine learning for fiber-induced nonlinearity mitigation in long-haul coherent optical OFDM
(2018-12-20)
Coherent optical orthogonal frequency division multiplexing (CO-OFDM) has attracted a lot of interest in optical fiber communications due to its simplified digital signal processing (DSP) units, high spectral-efficiency, ...
Predicting EHL film thickness parameters by machine learning approaches
(2022)
Non-dimensional similarity groups and analytically solvable proximity equations can be used to estimate integral fluid film parameters of elastohydrodynamically lubricated (EHL) contacts. In this contribution, we demonstrate ...