Results 21 to 30 of about 1,606,312 (290)
Learning with Differentiable Algorithms
CoRR, 2022 PhD thesis (summa cum laude), University of Konstanz, 162 ...
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A New Online Learned Interval Type-3 Fuzzy Control System for Solar Energy Management Systems
IEEE Access, 2021 In this article, a novel method based on interval type-3 fuzzy logic systems (IT3-FLSs) and an online learning approach is designed for power control and battery charge planing for photovoltaic (PV)/battery hybrid systems.
Zhi Liu +5 more
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Overview of Spiking Neural Network Learning Approaches and Their Computational Complexities
Sensors, 2023 Spiking neural networks (SNNs) are subjects of a topic that is gaining more and more interest nowadays. They more closely resemble actual neural networks in the brain than their second-generation counterparts, artificial neural networks (ANNs). SNNs have
Paweł Pietrzak +3 more
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Joint Learning of Generative Translator and Classifier for Visually Similar Classes
IEEE Access, 2020 In this paper, we propose a Generative Translation Classification Network (GTCN) for improving visual classification accuracy in settings where classes are visually similar and data is scarce. For this purpose, we propose joint learning from a scratch to
Byungin Yoo +3 more
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Basis exchange and learning algorithms for extracting collinear patterns
Journal of Information and Telecommunication, 2021 Understanding large data sets is one of the most important and challenging problems in the modern days. Exploration of genetic data sets composed of high dimensional feature vectors can be treated as a leading example in this context.
Leon Bobrowski, Paweł Zabielski
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Online Learning Algorithms [PDF]
Foundations of Computational Mathematics, 2005 In this paper, we study an online learning algorithm in Reproducing Kernel Hilbert Spaces (RKHSs) and general Hilbert spaces. We present a general form of the stochastic gradient method to minimize a quadratic potential function by an independent identically distributed (i.i.d.) sample sequence, and show a probabilistic upper bound for its convergence.
Smale, Steve, Yao, Yuan
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Learning Algorithms for Active Learning
CoRR, 2017 Accepted for publication at ICML ...
Philip Bachman +2 more
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Ensemble Algorithms in Reinforcement Learning [PDF]
IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics), 2008 This paper describes several ensemble methods that combine multiple different reinforcement learning (RL) algorithms in a single agent. The aim is to enhance learning speed and final performance by combining the chosen actions or action probabilities of different RL algorithms.
Marco A. Wiering, Hado van Hasselt
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Machine Learning Methods for Attack Detection in the Smart Grid [PDF]
, 2015 Attack detection problems in the smart grid are posed as statistical learning problems for different attack scenarios in which the measurements are observed in batch or online settings.
Esnaola, Inaki +4 more
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Decoding the grasping intention from electromyography during reaching motions
Journal of NeuroEngineering and Rehabilitation, 2018 Background Active upper-limb prostheses are used to restore important hand functionalities, such as grasping. In conventional approaches, a pattern recognition system is trained over a number of static grasping gestures. However, training a classifier in
Iason Batzianoulis +4 more
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