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Analysis, 2022
Abstract Numerous computational and learning theory models have been studied using probabilistic functional equations. Especially in two-choice scenarios, the vast bulk of animal behavior research divides such situations into two different events. They split these actions into two possibilities according to the animals’ progress toward a
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Abstract Numerous computational and learning theory models have been studied using probabilistic functional equations. Especially in two-choice scenarios, the vast bulk of animal behavior research divides such situations into two different events. They split these actions into two possibilities according to the animals’ progress toward a
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2017 10th International Workshop on Multidimensional (nD) Systems (nDS), 2017
Iterative learning control can be applied to systems that execute the same finite duration task over and over again. This method control has been applied to many engineering systems, such as gantry robots and electrical motors. This paper gives further results on the design of dynamic iterative learning control laws using the repetitive process setting
Eric Rogers +2 more
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Iterative learning control can be applied to systems that execute the same finite duration task over and over again. This method control has been applied to many engineering systems, such as gantry robots and electrical motors. This paper gives further results on the design of dynamic iterative learning control laws using the repetitive process setting
Eric Rogers +2 more
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On the Stability-Plasticity Dilemma in Continual Meta-Learning: Theory and Algorithm
Advances in Neural Information Processing Systems 36, 2023Qi Chen 0015 +3 more
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2011 IEEE International Symposium on Intelligent Control, 2011
This paper considers iterative learning control for the practically relevant case of deterministic discrete linear plants where the first Markov parameter is zero. A 2D systems approach that uses a strong form of stability for linear repetitive processes is used to develop a one step control law design for both trial-to-trial error convergence and ...
Lukasz Hladowski +5 more
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This paper considers iterative learning control for the practically relevant case of deterministic discrete linear plants where the first Markov parameter is zero. A 2D systems approach that uses a strong form of stability for linear repetitive processes is used to develop a one step control law design for both trial-to-trial error convergence and ...
Lukasz Hladowski +5 more
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Stability of spectral learning algorithms: theory, methodologies and applications
In Data Mining an important research problem is the identification and analysis of theoretical properties that characterize and explain the behavior of learning algorithms. Based on such theoretical tools the comparison and analysis of algorithms can be based on rigorous and sound criteria other than simply their empirical behavior. In this context, anopenaire +2 more sources
Educational Architecture: A Human Conditions Theory of Learning System Stability
<p><span>Education reform has historically focused on curriculum, instructional practice, and accountability systems used to measure academic performance. While these approaches have generated valuable insights into teaching and learning, they often overlook the upstream conditions that regulate learning itself.openaire +1 more source
2006
This thesis studies two key properties of learning algorithms: their generalization ability and their stability with respect to perturbations. To analyze these properties, we focus on concentration inequalities and tools from empirical process theory. We obtain theoretical results and demonstrate their applications to machine learning.
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This thesis studies two key properties of learning algorithms: their generalization ability and their stability with respect to perturbations. To analyze these properties, we focus on concentration inequalities and tools from empirical process theory. We obtain theoretical results and demonstrate their applications to machine learning.
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On the stability of two functional equations arising in mathematical biology and theory of learning
Creative Mathematics and Informatics, 2019AYNUR SAHIN, HAKAN ARISOY, ZEYNEP KALKAN
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MACHINE LEARNING APPROACHES IN GEOTECHNICAL ENGINEERING: THEORY AND PRACTICE FOR SLOPE STABILIZATION
2020null Mihir Bharatkumar Anjaria, Lakshya Sahai +2 more
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Safe Reinforcement Learning With Stability Guarantee for Motion Planning of Autonomous Vehicles
IEEE Transactions on Neural Networks and Learning Systems, 2021Ye Zhao, Minghao Han, Lixian Zhang
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