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Akademický článek
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Autor:
Manta, Michael N., Soberón, Pablo
We generalize the Yao-Yao partition theorem by showing that for any smooth measure in $R^d$ there exist equipartitions using $(t+1)2^{d-1}$ convex regions such that every hyperplane misses the interior of at least $t$ regions. In addition, we present
Externí odkaz:
http://arxiv.org/abs/2107.06233
Akademický článek
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It is a long standing open problem whether Yao-Yao graphs $\mathsf{YY}_{k}$ are all spanners [li2002sparse]. Bauer and Damian [bauer2013infinite] showed that all $\mathsf{YY}_{6k}$ for $k \geq 6$ are spanners. Li and Zhan [li2016almost] generalized t
Externí odkaz:
http://arxiv.org/abs/1704.03132
It is an open problem whether Yao-Yao graphs $\mathsf{YY}_k$ (also known as sparse-Yao graphs) are all spanners when the integer parameter $k$ is large enough. In this paper we show that, for any integer $k\geq 42$, the Yao-Yao graph $\mathsf{YY}_{2k
Externí odkaz:
http://arxiv.org/abs/1604.05814
Autor:
Cui, Jiahao, Li, Hui, Yao, Yao, Zhu, Hao, Shang, Hanlin, Cheng, Kaihui, Zhou, Hang, Zhu, Siyu, Wang, Jingdong
Recent advances in latent diffusion-based generative models for portrait image animation, such as Hallo, have achieved impressive results in short-duration video synthesis. In this paper, we present updates to Hallo, introducing several design enhanc
Externí odkaz:
http://arxiv.org/abs/2410.07718
In the real world, a learning-enabled system usually undergoes multiple cycles of model development to enhance the system's ability to handle difficult or emerging tasks. This continual model development process raises a significant issue that the mo
Externí odkaz:
http://arxiv.org/abs/2410.03955
Autor:
Zhuang, Yiyu, He, Yuxiao, Zhang, Jiawei, Wang, Yanwen, Zhu, Jiahe, Yao, Yao, Zhu, Siyu, Cao, Xun, Zhu, Hao
Creating 3D head avatars is a significant yet challenging task for many applicated scenarios. Previous studies have set out to learn 3D human head generative models using massive 2D image data. Although these models are highly generalizable for human
Externí odkaz:
http://arxiv.org/abs/2410.01226
Large language models (LLMs) have rapidly advanced and demonstrated impressive capabilities. In-Context Learning (ICL) and Parameter-Efficient Fine-Tuning (PEFT) are currently two mainstream methods for augmenting LLMs to downstream tasks. ICL typica
Externí odkaz:
http://arxiv.org/abs/2409.20181
For the 2D incompressible Euler equations, we establish global-in-time ($t \in \mathbb{R}$) stability of vortex quadrupoles satisfying odd symmetry with respect to both axes. Specifically, if the vorticity restricted to a quadrant is signed, sufficie
Externí odkaz:
http://arxiv.org/abs/2409.19822