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搜索结果: 1-15 共查到会议中心 e-Learning相关记录63条 . 查询时间(0.054 秒)
The analysis of data stored in multiple sites has become more popular, raising new concerns about the security of data storage and communication. Federated learning, which does not require centralizin...
The explosion of spatiotemporal data in the physical world requires new deep learning tools to model complex dynamical systems.
Despite widespread use in online transactions, rating systems only provide summary statistics of buyers' diverse opinions at best. To investigate the consequences of this coarse form of information ag...
Differential privacy is one of the most common techniques in privacy-preserving machine learning due to its rigorous math definition and theoretical results. Transfer learning and Federated learning a...
In this talk, I will present our recent work on the convergence/generalization analysis for the popular optimizers in deep learning. (1) We establish the convergence for Adam under (L0,L1 ) smoothness...
Nonlinear dynamics play a prominent role in many domains and are notoriously difficult to solve. Whereas previous quantum algorithms for general nonlinear equations have been severely limited due to t...
A fundamental problem from computational learning theory is to well-reconstruct an unknown function on the discrete hypercubes. One classical result of this problem for the random query model is the l...
This report consists of two parts associated with graph neural networks: generalization and graph structural learning. We first study the Rademacher complexity of GNNs, as one of independent-algorithm...
In this paper we apply economic narratives to inflation forecasting using a large news corpus and machine learning algorithms. We measure economic narratives quantitatively from the full text content ...
In this talk, we present our work on structure-preserving machine learning (ML) moment closure models for the radiative transfer equation. Most of the existing ML closure models are not able to guaran...
Tool path planning is a crucial factor of computer-aided design and manufacturing (CAD/CAM). To generate suitable tool paths, the previous methods often transform the problem into local or global opti...
Solving multi-scale PDEs is difficult in high-dimensional and/or convection-dominant cases. The interacting particle methods (IPM) are shown to outperform solving PDEs directly. Examples include compu...
本次讲座主要针对智能运维中的建模优化问题。首先基于前期研究,我将讨论基于马尔可夫决策过程的有限周期的视情维护策略。考虑二元件系统以及系统元件的退化过程具有随机相关性,用二元伽马过程来描述系统退化过程。系统元件服从周期性检测,当元件的退化程度超过预防性维护阈值时,其会被替换。该维护问题可以表示成马尔可夫决策过程并可用动态规划来求解。不同于无限周期的维护策略,有限周期的最优策略是动态的,其在每次检测都...
本次讲座主要针对智能运维中的建模优化问题。首先基于前期研究,我将讨论基于马尔可夫决策过程的有限周期的视情维护策略。考虑二元件系统以及系统元件的退化过程具有随机相关性,用二元伽马过程来描述系统退化过程。系统元件服从周期性检测,当元件的退化程度超过预防性维护阈值时,其会被替换。该维护问题可以表示成马尔可夫决策过程并可用动态规划来求解。不同于无限周期的维护策略,有限周期的最优策略是动态的,其在每次检测都...
Why do neural networks (NN) that look so complex usually generalize well? To understand this problem, we find some simple implicit regularizations during training NNs. The first is the frequency princ...

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