Zobrazeno 1 - 10
of 12 719
pro vyhledávání: '"ZHOU, QING"'
Autor:
Tan, Bo, Zhou, Qing-Long
We fill a gap in the study of the Hausdorff dimension of the set of exact approximation order considered by Fregoli [Proc. Amer. Math. Soc. 152 (2024), no. 8, 3177--3182].
Externí odkaz:
http://arxiv.org/abs/2411.18439
Autor:
Tan, Bo, Zhou, Qing-Long
In this paper, we answer a question of Cai-Hambrook in (arXiv$\colon$ 2403.19410). Furthermore, we compute the Fourier dimension of the multiplicative $\psi$-well approximable set $$M_2^{\times}(\psi)=\left\{(x_1,x_2)\in [0,1]^{2}\colon \|qx_1\|\|qx_
Externí odkaz:
http://arxiv.org/abs/2409.12557
Autor:
Tan, Bo, Zhou, Qing-Long
Let $E\subset [0,1]$ be a set that supports a probability measure $\mu$ with the property that $|\widehat{\mu}(t)|\ll (\log |t|)^{-A}$ for some constant $A>2.$ Let $\mathcal{A}=(q_n)_{n\in \N}$ be a positive, real-valued, lacunary sequence. We presen
Externí odkaz:
http://arxiv.org/abs/2409.03331
Accurate behavior prediction for vehicles is essential but challenging for autonomous driving. Most existing studies show satisfying performance under regular scenarios, but most neglected safety-critical scenarios. In this study, a spatio-temporal d
Externí odkaz:
http://arxiv.org/abs/2408.01774
Publikováno v:
A&A 690, A390 (2024)
The statistics of Einstein radii for a sample of strong lenses can provide valuable constraints on the underlying mass distribution. The correct interpretation, however, relies critically on the modelling of the selection of the sample, which has pro
Externí odkaz:
http://arxiv.org/abs/2406.17019
Brain tumor segmentation remains a significant challenge, particularly in the context of multi-modal magnetic resonance imaging (MRI) where missing modality images are common in clinical settings, leading to reduced segmentation accuracy. To address
Externí odkaz:
http://arxiv.org/abs/2406.08634
From paired image-text training to text-only training for image captioning, the pursuit of relaxing the requirements for high-cost and large-scale annotation of good quality data remains consistent. In this paper, we propose Text-only Synthesis for I
Externí odkaz:
http://arxiv.org/abs/2405.18258
Autor:
Smith, Stephen, Zhou, Qing
Learning the structure of causal directed acyclic graphs (DAGs) is useful in many areas of machine learning and artificial intelligence, with wide applications. However, in the high-dimensional setting, it is challenging to obtain good empirical and
Externí odkaz:
http://arxiv.org/abs/2405.15358
Few-shot learning aims to generalize the recognizer from seen categories to an entirely novel scenario. With only a few support samples, several advanced methods initially introduce class names as prior knowledge for identifying novel classes. Howeve
Externí odkaz:
http://arxiv.org/abs/2405.12543
Publikováno v:
Julius-Kühn-Archiv, Vol 463, Iss 1, Pp 211-216 (2018)
To understand the diversity of stored grain insects in northwest China, we have fulfilled insect collection in 56 grain storage enterprises, 60 grain, oil and feed processing plants and 65 farmers situated in 26 cities of five provinces (Shaanxi, Gan
Externí odkaz:
https://doaj.org/article/4c70714f594b49bc9e8a643b25dff142
