Zobrazeno 1 - 10
of 498
pro vyhledávání: '"Peng, Bei"'
Generative Commonsense Reasoning (GCR) requires a model to reason about a situation using commonsense knowledge, while generating coherent sentences. Although the quality of the generated sentences is crucial, the diversity of the generation is equal
Externí odkaz:
http://arxiv.org/abs/2404.16807
ChatGPT, as a language model based on large-scale pre-training, has exerted a profound influence on the domain of machine translation. In ChatGPT, a "Prompt" refers to a segment of text or instruction employed to steer the model towards generating a
Externí odkaz:
http://arxiv.org/abs/2401.09984
In the classical Kalman filter(KF), the estimated state is a linear combination of the one-step predicted state and measurement state, their confidence level change when the prediction mean square error matrix and covariance matrix of measurement noi
Externí odkaz:
http://arxiv.org/abs/2309.09565
In multi-target tracking (MTT), non-Gaussian measurement noise from sensors can diminish the performance of the Gaussian-assumed Gaussian mixture probability hypothesis density (GM-PHD) filter. In this paper, an approach that transforms the MTT probl
Externí odkaz:
http://arxiv.org/abs/2309.08088
Prior work has shown that the ordering in which concepts are shown to a commonsense generator plays an important role, affecting the quality of the generated sentence. However, it remains a challenge to determine the optimal ordering of a given set o
Externí odkaz:
http://arxiv.org/abs/2309.06363
The information transmission between nodes in a wireless sensor networks (WSNs) often causes packet loss due to denial-of-service (DoS) attack, energy limitations, and environmental factors, and the information that is successfully transmitted can al
Externí odkaz:
http://arxiv.org/abs/2307.01445
The robustness of the kernel recursive least square (KRLS) algorithm has recently been improved by combining them with more robust information-theoretic learning criteria, such as minimum error entropy (MEE) and generalized MEE (GMEE), which also imp
Externí odkaz:
http://arxiv.org/abs/2307.01442
In real applications, non-Gaussian distributions are frequently caused by outliers and impulsive disturbances, and these will impair the performance of the classical cubature Kalman filter (CKF) algorithm. In this letter, a modified generalized minim
Externí odkaz:
http://arxiv.org/abs/2307.01438
The distributed Kalman filter (DKF) has attracted extensive research as an information fusion method for wireless sensor systems(WSNs). And the DKF in non-Gaussian environments is still a pressing problem. In this paper, we approximate the non-Gaussi
Externí odkaz:
http://arxiv.org/abs/2306.11476
This paper investigates how deep multi-agent reinforcement learning can enable the scalable and privacy-preserving coordination of residential energy flexibility. The coordination of distributed resources such as electric vehicles and heating will be
Externí odkaz:
http://arxiv.org/abs/2305.18875