Results 61 to 70 of about 82,244 (222)

Quasi Grand Lebesgue Spaces

, 2020
We introduce a new class of quasi-Banach spaces as an extension of the classical Grand Lebesgue Spaces for small values of the parameter, and we investigate some its properties, in particular, completeness, fundamental function, operators estimates, Boyd indices, contraction principle, tail behavior, dual space, generalized triangle and quadrilateral ...
Formica, Maria Rosaria, Ostrovsky, Eugeny, Sirota, Leonid   +2 more
openaire   +2 more sources

Coevolutionary Neural Dynamics With Learnable Parameters for Nonconvex Optimisation

CAAI Transactions on Intelligence Technology, EarlyView.
ABSTRACT Nonconvex optimisation plays a crucial role in science and industry. However, existing methods often encounter local optima or provide inferior solutions when solving nonconvex optimisation problems, lacking robustness in noise scenarios. To address these limitations, we aim to develop a robust, efficient and globally convergent solver for ...
Yipiao Chen, Wenbin Du, Huichao Cao, Long Jin   +3 more
wiley   +1 more source

$$\theta$$-Lebesgue spaces

Journal of Mathematical Sciences
Traditional Lp spaces are fundamental in functional analysis, demarcated by the relationship $1/p + 1/q = 1$. This research pioneers the concept of $\theta$-Lebesgue space, stemming from a simultaneous weakening of both the classical $L_p$ relation and its $\theta$-variant, $1/(\theta(p)) + 1/(\theta(q)) = 1$.
openaire   +3 more sources

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, Xin Xu, Yixing Lan, Tenglong Liu, Yueying Wang   +4 more
wiley   +1 more source

Global gradient estimates for Dirichlet problems of elliptic operators with a BMO antisymmetric part

Advances in Nonlinear Analysis, 2022
Let n≥2n\ge 2 and Ω⊂Rn\Omega \subset {{\mathbb{R}}}^{n} be a bounded nontangentially accessible domain. In this article, the authors investigate (weighted) global gradient estimates for Dirichlet boundary value problems of second-order elliptic equations
Yang Sibei, Yang Dachun, Yuan Wen
doaj   +1 more source

Norm convolution inequalities in Lebesgue spaces [PDF]

Revista Matemática Iberoamericana, 2018
We obtain upper and similar lower estimates of the ( L_p, L_q ) norm for the convolution operator. The upper estimate improves on known convolution inequalities.
Nursultanov E., Tikhonov S., Tleukhanova N.   +2 more
openaire   +4 more sources

Quantitative Evaluation of Mechanical Defects for Circuit Breakers Based on Self‐Adaptive Fault Feature Tracking

High Voltage, EarlyView.
ABSTRACT Many researchers are committed to improving the diagnosis accuracy and solving the few‐shot problem on circuit breakers (CBs). However, the research on the vibration transmission mechanism of the fault is insufficient, which makes it difficult to find the potential design defects of CBs through vibration.
Jiayi Gong, Yaxiong Tan, Shangding Li, Jian Li   +3 more
wiley   +1 more source

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, Hans Friedrich Köhn, Chia‐Yi Chiu   +2 more
wiley   +1 more source

Miners' Reward Elasticity and Stability of Competing Proof‐of‐Work Cryptocurrencies

International Economic Review, EarlyView.
ABSTRACT Proof‐of‐Work cryptocurrencies employ miners to sustain the system through algorithmic reward adjustments. We develop a stochastic model of the multicurrency mining and identify conditions for stable transaction speeds. Bitcoin's algorithm requires hash supply elasticity <$<$1 for stability, while ASERT remains stable for any elasticity and ...
Kohei Kawaguchi, Junpei Komiyama, Shunya Noda   +2 more
wiley   +1 more source

Alternative Approaches for Estimating Highest‐Density Regions

International Statistical Review, EarlyView.
Summary Among the variety of statistical intervals, highest‐density regions (HDRs) stand out for their ability to effectively summarise a distribution or sample, unveiling its distinctive and salient features. An HDR represents the minimum size set that satisfies a certain probability coverage, and current methods for their computation require ...
Nina Deliu, Brunero Liseo
wiley   +1 more source