Results 51 to 60 of about 2,217 (207)
Commutators of multilinear strongly singular integrals on nonhomogeneous metric measure spaces
Open Mathematics, 2021 Let (X,d,μ)\left(X,d,\mu ) denote nonhomogeneous metric measure space satisfying geometrically doubling and the upper doubling measure conditions.
Wang Hailian, Xie Rulong
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AGT: Efficient Offline Reinforcement Learning With Advantage‐Guided Transformer
CAAI Transactions on Intelligence Technology, EarlyView.ABSTRACT Offline reinforcement learning (RL) is a paradigm that seeks to train policies directly based on fixed datasets derived from previous interactions with the environment. However, offline RL faces critical challenges in environments characterised by sparse rewards and datasets dominated by suboptimal trajectories.
Jiaye Wei +4 more
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Open Mathematics, 2017 The main purpose of this paper is to prove that the boundedness of the commutator Mκ,b∗$\mathcal{M}_{\kappa,b}^{*} $ generated by the Littlewood-Paley operator Mκ∗$\mathcal{M}_{\kappa}^{*} $ and RBMO (μ) function on non-homogeneous metric measure ...
Lu Guanghui, Tao Shuangping
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Identifiability conditions in cognitive diagnosis: Implications for Q‐matrix estimation algorithms
British Journal of Mathematical and Statistical Psychology, EarlyView.Abstract The Q‐matrix of a cognitively diagnostic assessment (CDA), documenting the item‐attribute associations, is a key component of any CDA. However, the true Q‐matrix underlying a CDA is never known and must be estimated—typically by content experts.
Hyunjoo Kim +2 more
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Open Mathematics, 2015 The paper presents a new type of density topology on the real line generated by the pointwise convergence, similarly to the classical density topology which is generated by the convergence in measure.
Górajska Magdalena
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Calibrating Bayesian inference
British Journal of Mathematical and Statistical Psychology, EarlyView.Abstract Bayesian statistics has gained popularity in psychological research due to its intuitive uncertainty quantification and convenient information‐updating rules. In many applications, however, prior distributions are introduced merely as instruments to facilitate computation, rather than as representations of genuine subjective belief ...
Yang Liu +2 more
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Journal of Mathematics, 2017 One of the goals of this article is to describe a setting adapted to the description of means (normalized integrals or invariant means) on an infinite product of measured spaces with infinite measure and of the concentration property on metric measured ...
Jean-Pierre Magnot
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On Spatial Point Processes With Composition‐Valued Marks
International Statistical Review, EarlyView.Summary Methods for marked spatial point processes with scalar marks have seen extensive development in recent years. While the impressive progress in data collection and storage capacities has yielded an immense increase in spatial point process data with highly challenging non‐scalar marks, methods for their analysis are not equally well developed ...
Matthias Eckardt +2 more
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Identification of Fully Measurable Grand Lebesgue Spaces
Journal of Function Spaces, 2017 We consider the Banach function spaces, called fully measurable grand Lebesgue spaces, associated with the function norm ρ(f)=ess supx∈Xδ(x)ρp(x)(f), where ρp(x) denotes the norm of the Lebesgue space of exponent p(x), and p(·) and δ(·) are measurable ...
Giuseppina Anatriello +2 more
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Asymptotics of Time‐Varying Processes in Continuous‐Time Using Locally Stationary Approximations
Journal of Time Series Analysis, EarlyView.ABSTRACT We introduce a general theory on stationary approximations for locally stationary continuous‐time processes. Based on the stationary approximation, we use θ$$ \theta $$‐weak dependence to establish laws of large numbers and central limit type results under different observation schemes.
Robert Stelzer, Bennet Ströh
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