LAUSR

Multivariable nonparametric learning: A robust iterative inversion‐based control approach

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0 Published in 2020 at "International Journal of Robust and Nonlinear Control"

DOI: 10.1002/rnc.5287

Abstract: Learning control enables significant performance improvement for systems by utilizing past data. Typical design methods aim to achieve fast convergence by using prior system knowledge in the form of a parametric model. To ensure that… read more here.

Keywords: learning robust; robust iterative; multivariable nonparametric; approach ... See more keywords

Online learning robust MPC: an exploration-exploitation approach

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0 Published in 2020 at "IFAC-PapersOnLine"

DOI: 10.1016/j.ifacol.2020.12.1210

Abstract: This paper presents a predictive controller whose model is based on input-output data of the nonlinear system to be controlled. It uses a Lipschitz interpolation technique in which new data may be included in the… read more here.

Keywords: learning robust; robust mpc; exploration exploitation; exploration ... See more keywords

Active playful learning as a robust, adaptable, culturally relevant pedagogy to foster children’s 21st century skills

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0 Published in 2024 at "Journal of Children and Media"

DOI: 10.1080/17482798.2024.2356956

Abstract: ABSTRACT Drawing upon Vygotskian and Piagetian learning theories, recent research reveals children’s learning can be maximized through a specific Active Playful Learning (APL) approach called guided play. The deepest and most engaging learning happens during… read more here.

Keywords: robust adaptable; play; playful learning; learning robust ... See more keywords

Leveraging advances in machine learning for the robust classification and interpretation of networks

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0 Published in 2024 at "Royal Society Open Science"

DOI: 10.1098/rsos.240458

Abstract: The ability to simulate realistic networks based on empirical data is an important task across scientific disciplines, from epidemiology to computer science. Often, simulation approaches involve selecting a suitable network generative model such as Erdös–Rényi… read more here.

Keywords: advances machine; machine learning; learning robust; network ... See more keywords

Learning Robust LQ-Controllers Using Application Oriented Exploration

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0 Published in 2020 at "IEEE Control Systems Letters"

DOI: 10.1109/lcsys.2019.2921512

Abstract: This letter concerns the problem of learning robust LQ-controllers, when the dynamics of the linear system are unknown. First, we propose a robust control synthesis method to minimize the worst-case LQ cost, with probability $1-\delta… read more here.

Keywords: learning robust; controller; exploration; worst case ... See more keywords

Deep Multiple Instance Convolutional Neural Networks for Learning Robust Scene Representations

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0 Published in 2020 at "IEEE Transactions on Geoscience and Remote Sensing"

DOI: 10.1109/tgrs.2019.2960889

Abstract: The accuracy and efficiency of scene classification have immensely improved with the extensive application of deep convolutional neural networks (CNNs). However, standard CNNs classify images mostly based on the global features from the last fully… read more here.

Keywords: learning robust; multiple instance; neural networks; instance ... See more keywords

Learning Robust Predictive Control: A Spatial–Temporal Game Theoretic Approach

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0 Published in 2024 at "IEEE Transactions on Neural Networks and Learning Systems"

DOI: 10.1109/tnnls.2024.3357238

Abstract: This article investigates robust predictive control problem for unknown dynamical systems. Since the dynamics unavailability restricts feasibility of model-driven methods, learning robust predictive control (LRPC) framework is developed from the aspect of time consistency. Under… read more here.

Keywords: time; control; robust predictive; predictive control ... See more keywords

Deep Learning for Robust ARIS-aided Multiuser MIMO Networks with Channel Uncertainty

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0 Published in 2025 at "IEEE Transactions on Wireless Communications"

DOI: 10.1109/twc.2025.3622125

Abstract: This work addresses the problem of joint robust transmission, reflection, and reception strategy design in an active reconfigurable intelligent surface (ARIS)-assisted multiuser multiple-input multiple-output (MIMO) system. Specifically, a signal-to-interference-noise (SINR) maximization problem has been formulated… read more here.

Keywords: deep learning; robust aris; learning robust; model ... See more keywords