Zobrazeno 1 - 10
of 65
pro vyhledávání: '"Qin, Yuzhen"'
Although deep reinforcement learning (DRL) approaches in audio signal processing have seen substantial progress in recent years, audio-driven DRL for tasks such as navigation, gaze control and head-orientation control in the context of human-robot in
Externí odkaz:
http://arxiv.org/abs/2409.10048
The stability of complex networks, from power grids to biological systems, is crucial for their proper functioning. It is thus important to control such systems to maintain or restore their stability. Traditional approaches rely on real-time state me
Externí odkaz:
http://arxiv.org/abs/2408.08263
Epilepsy is one of the most common neurological disorders globally, affecting millions of individuals. Despite significant advancements, the precise mechanisms underlying this condition remain largely unknown, making accurately predicting and prevent
Externí odkaz:
http://arxiv.org/abs/2404.03409
Cluster synchronization is of paramount importance for the normal functioning of numerous technological and natural systems. Deviations from normal cluster synchronization patterns are closely associated with various malfunctions, such as neurologica
Externí odkaz:
http://arxiv.org/abs/2308.07302
Autor:
Nobili, Alberto Maria, Qin, Yuzhen, Avizzano, Carlo Alberto, Bassett, Danielle S., Pasqualetti, Fabio
Publikováno v:
Proceedings of the 2022 American Control Conference, San Diego, May, 2022
Many natural and man-made network systems need to maintain certain patterns, such as working at equilibria or limit cycles, to function properly. Thus, the ability to stabilize such patterns is crucial. Most of the existing studies on stabilization a
Externí odkaz:
http://arxiv.org/abs/2308.05823
The growing interest in complex decision-making and language modeling problems highlights the importance of sample-efficient learning over very long horizons. This work takes a step in this direction by investigating contextual linear bandits where t
Externí odkaz:
http://arxiv.org/abs/2302.00814
The widespread emergence of smart devices for ECG has sparked demand for intelligent single-lead ECG-based diagnostic systems. However, it is challenging to develop a single-lead-based ECG interpretation model for multiple diseases diagnosis due to t
Externí odkaz:
http://arxiv.org/abs/2301.12178
Humans are capable of adjusting to changing environments flexibly and quickly. Empirical evidence has revealed that representation learning plays a crucial role in endowing humans with such a capability. Inspired by this observation, we study represe
Externí odkaz:
http://arxiv.org/abs/2205.05820
Cluster synchronization underlies various functions in the brain. Abnormal patterns of cluster synchronization are often associated with neurological disorders. Deep brain stimulation (DBS) is a neurosurgical technique used to treat several brain dis
Externí odkaz:
http://arxiv.org/abs/2204.00678
In this paper, we study representation learning for multi-task decision-making in non-stationary environments. We consider the framework of sequential linear bandits, where the agent performs a series of tasks drawn from distinct sets associated with
Externí odkaz:
http://arxiv.org/abs/2201.04805