Zobrazeno 1 - 10
of 377
pro vyhledávání: '"KONG Weiwei"'
Publikováno v:
Xibei zhiwu xuebao, Vol 44, Iss 2, Pp 229-235 (2024)
Abstract [Objective] The transcription factor ERF has various biological functions, and plays important roles in regulating plant growth, development and responding to stress. Previous studies have shown that SmERF1 from Salvia miltiorrhiza was inv
Externí odkaz:
https://doaj.org/article/dd2129b850ae4ee2a12df13e701150b9
Publikováno v:
Journal of Medical Biochemistry, Vol 40, Iss 1, Pp 86-91 (2021)
Background: Nonalcoholic fatty liver disease (NAFLD) affects human health worldwide. Our objective was to explore the correlation between urinary retinol-binding protein (URBP) and NAFLD. Methods: This cross-sectional study included 445 NAFLD patient
Externí odkaz:
https://doaj.org/article/4538631a25ea46e684753cdbb68168e9
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
Autor:
Kong, Weiwei, Ribero, Mónica
Differentially-private stochastic gradient descent (DP-SGD) is a family of iterative machine learning training algorithms that privatize gradients to generate a sequence of differentially-private (DP) model parameters. It is also the standard tool us
Externí odkaz:
http://arxiv.org/abs/2407.05237
Vehicle platoon often face the problem of lack of scalability of maneuvers in practical applications. Once a new scenario is added, the original program may no longer be available. To deal with this problem, this paper introduces a two-dimensional ma
Externí odkaz:
http://arxiv.org/abs/2207.01167
Autor:
Kong, Weiwei
This paper develops and analyzes an accelerated proximal descent method for finding stationary points of nonconvex composite optimization problems. The objective function is of the form $f+h$ where $h$ is a proper closed convex function, $f$ is a dif
Externí odkaz:
http://arxiv.org/abs/2205.13055
Publikováno v:
In Journal of Cleaner Production 10 November 2024 479
Autor:
Kong, Weiwei, Monteiro, Renato D. C.
This paper proposes and analyzes a dampened proximal alternating direction method of multipliers (DP.ADMM) for solving linearly-constrained nonconvex optimization problems where the smooth part of the objective function is nonseparable. Each iteratio
Externí odkaz:
http://arxiv.org/abs/2110.12502
Autor:
Kong, Weiwei, Monteiro, Renato D. C.
This paper proposes and analyzes an accelerated inexact dampened augmented Lagrangian (AIDAL) method for solving linearly-constrained nonconvex composite optimization problems. Each iteration of the AIDAL method consists of: (i) inexactly solving a d
Externí odkaz:
http://arxiv.org/abs/2110.11151
Publikováno v:
In Polymer 3 June 2024 304