Zobrazeno 1 - 10
of 8 348
pro vyhledávání: '"BIE, P."'
Neural audio codecs have significantly advanced audio compression by efficiently converting continuous audio signals into discrete tokens. These codecs preserve high-quality sound and enable sophisticated sound generation through generative models tr
Externí odkaz:
http://arxiv.org/abs/2409.11228
We explore tree-based macroeconomic regime-switching in the context of the dynamic Nelson-Siegel (DNS) yield-curve model. In particular, we customize the tree-growing algorithm to partition macroeconomic variables based on the DNS model's marginal li
Externí odkaz:
http://arxiv.org/abs/2408.12863
Autor:
Amin, Kareem, Bie, Alex, Kong, Weiwei, Kurakin, Alexey, Ponomareva, Natalia, Syed, Umar, Terzis, Andreas, Vassilvitskii, Sergei
We present an approach for generating differentially private synthetic text using large language models (LLMs), via private prediction. In the private prediction framework, we only require the output synthetic data to satisfy differential privacy gua
Externí odkaz:
http://arxiv.org/abs/2407.12108
In this paper, we show that a Clifford algebra valued function is slice if and only if it is in the kernel of Dunkl-spherical Dirac operator and a slice function $f$ is slice regular if and only if it is in the kernel of the Dunkl-Cauchy-Riemann oper
Externí odkaz:
http://arxiv.org/abs/2407.06811
We examine the relationship between learnability and robust (or agnostic) learnability for the problem of distribution learning. We show that, contrary to other learning settings (e.g., PAC learning of function classes), realizable learnability of a
Externí odkaz:
http://arxiv.org/abs/2406.17814
Autor:
Heiter, Edith, Martens, Liesbet, Seurinck, Ruth, Guilliams, Martin, De Bie, Tijl, Saeys, Yvan, Lijffijt, Jefrey
This paper presents TRACE, a tool to analyze the quality of 2D embeddings generated through dimensionality reduction techniques. Dimensionality reduction methods often prioritize preserving either local neighborhoods or global distances, but insights
Externí odkaz:
http://arxiv.org/abs/2406.12953
Personalized recommendation systems often drive users towards more extreme content, exacerbating opinion polarization. While (content-aware) moderation has been proposed to mitigate these effects, such approaches risk curtailing the freedom of speech
Externí odkaz:
http://arxiv.org/abs/2405.18941
Publikováno v:
IEEE Access ( Volume: 11, 2023) Page(s): 117971 - 117983
Representing the nodes of continuous-time temporal graphs in a low-dimensional latent space has wide-ranging applications, from prediction to visualization. Yet, analyzing continuous-time relational data with timestamped interactions introduces uniqu
Externí odkaz:
http://arxiv.org/abs/2405.17253
Publikováno v:
Appl. Sci. 2024, 14(8), 3516
Dynamic Link Prediction (DLP) addresses the prediction of future links in evolving networks. However, accurately portraying the performance of DLP algorithms poses challenges that might impede progress in the field. Importantly, common evaluation pip
Externí odkaz:
http://arxiv.org/abs/2405.17182
Autor:
Li, Zhonglin, Gao, Kangyu, Wang, Yingying, Bie, Ruitong, Yang, Dongliang, Yu, Tianze, Gao, Renxi, Liu, Wenjun, Zhong, Bo, Sun, Linfeng
Line-scan mode facilitates fast-speed and high-throughput imaging with developing a suitable optical transverse needle focus. Metasurface with periodic structures such as diffractive rings, ellipses, and gratings could enable discrete focus evolving
Externí odkaz:
http://arxiv.org/abs/2405.07136