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Progress towards Analytically Optimal Angles in Quantum Approximate Optimisation
Mathematics, 2022 The quantum approximate optimisation algorithm is a p layer, time variable split operator method executed on a quantum processor and driven to convergence by classical outer-loop optimisation.
Daniil Rabinovich +4 more
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Communications Biology, 2021 Teaching an assistive robotic manipulator to move objects in a cluttered table requires demonstrations from expert operators, but what if the experts are individuals with motor disabilities? Batzianoulis et al.
Iason Batzianoulis +6 more
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Learning Optimal Fin-Ray Finger Design for Soft Grasping
Frontiers in Robotics and AI, 2021 The development of soft hands is an important progress to empower robotic grasping with passive compliance while greatly decreasing the complexity of control. Despite the advances during the past decades, it is still not clear how to design optimal hands
Zhifeng Deng, Miao Li, Miao Li
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BMC Ecology and Evolution, 2021 Background The SARS-CoV-2 pandemic is one of the greatest global medical and social challenges that have emerged in recent history. Human coronavirus strains discovered during previous SARS outbreaks have been hypothesized to pass from bats to humans ...
Vladimir Makarenkov +3 more
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ThriftyNets: Convolutional Neural Networks with Tiny Parameter Budget
IoT, 2021 Deep Neural Networks are state-of-the-art in a large number of challenges in machine learning. However, to reach the best performance they require a huge pool of parameters. Indeed, typical deep convolutional architectures present an increasing number of
Guillaume Coiffier +2 more
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Scientific Reports, 2023 During reaching actions, the human central nerve system (CNS) generates the trajectories that optimize effort and time. When there is an obstacle in the path, we make sure that our arm passes the obstacle with a sufficient margin.
Fumiaki Iwane +2 more
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Forgetting Enhances Episodic Control With Structured Memories
Frontiers in Computational Neuroscience, 2022 Forgetting is a normal process in healthy brains, and evidence suggests that the mammalian brain forgets more than is required based on limitations of mnemonic capacity. Episodic memories, in particular, are liable to be forgotten over time.
Annik Yalnizyan-Carson +7 more
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ALGORITHMIC TRADING WITH LEARNING [PDF]
International Journal of Theoretical and Applied Finance, 2013 We propose a model where an algorithmic trader takes a view on the distribution of prices at a future date and then decides how to trade in the direction of their predictions using the optimal mix of market and limit orders. As time goes by, the trader learns from changes in prices and updates their predictions to tweak their strategy.
Cartea, A, Jaimungal, S, Kinzebulatov, D
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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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