Zobrazeno 1 - 10
of 547
pro vyhledávání: '"Zhu, Mu"'
This paper introduces a novel approach, Decision Theory-guided Deep Reinforcement Learning (DT-guided DRL), to address the inherent cold start problem in DRL. By integrating decision theory principles, DT-guided DRL enhances agents' initial performan
Externí odkaz:
http://arxiv.org/abs/2402.06023
The stochastic block model (SBM) is a widely used framework for community detection in networks, where the network structure is typically represented by an adjacency matrix. However, conventional SBMs are not directly applicable to an adjacency matri
Externí odkaz:
http://arxiv.org/abs/2310.10952
We model time-varying network data as realizations from multivariate Gaussian distributions with precision matrices that change over time. To facilitate parameter estimation, we require not only that each precision matrix at any given time point be s
Externí odkaz:
http://arxiv.org/abs/2202.07099
Neural networks are suggested for learning a map from $d$-dimensional samples with any underlying dependence structure to multivariate uniformity in $d'$ dimensions. This map, termed DecoupleNet, is used for dependence model assessment and selection.
Externí odkaz:
http://arxiv.org/abs/2202.03406
Publikováno v:
In Expert Systems With Applications 1 October 2024 251
A fully nonparametric approach for making probabilistic predictions in multi-response regression problems is introduced. Random forests are used as marginal models for each response variable and, as novel contribution of the present work, the depende
Externí odkaz:
http://arxiv.org/abs/2112.03377
Defensive deception is a promising approach for cyber defense. Via defensive deception, the defender can anticipate attacker actions; it can mislead or lure attacker, or hide real resources. Although defensive deception is increasingly popular in the
Externí odkaz:
http://arxiv.org/abs/2101.10121
Defensive deception techniques have emerged as a promising proactive defense mechanism to mislead an attacker and thereby achieve attack failure. However, most game-theoretic defensive deception approaches have assumed that players maintain consisten
Externí odkaz:
http://arxiv.org/abs/2101.02863