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许多复杂生物系统可以由高维非线性动力系统描述,对原始数据进行降维有助于对这些系统进行有效分析。然而以一种可解释的方式进行极致低尺度的降维仍然是一个具有挑战性的问题。基于Takens延迟嵌入理论,将高维空间信息转换为低维时间信息,我们开发了极致低降维算法stPCA,并将其应用于重症监护医疗信息管理系统MIMIC-IIIMIMIC-IV数据集,提出了ICU病人的出院决策。stPCA基于ICU患者的高...
High-order interaction occurs in various complex network, such as social network, bionetwork and network medicine. Comparing with that there are a lot of well-developed math tools (from graph theory) ...
我们研究Stiefel流形上线性规划(LPS):其目标是线性函数,变量是p个n维空间正交向量(即Stiefel流形约束,p<=n),额外再满足k个线性约束。据我们所知,该模型首次被研究。k=0的(LPS)是一个经典的多项式可解问题。
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...
In this talk, a distributed stochastic gradient (SG) algorithm is proposed where the estimators are aimed to collectively estimate an unknown time-invariant parameter from a set of noisy measurements ...
Similar to the role of Markov decision processes in reinforcement learning, Markov games (also known as stochastic games) form the basis for the study of multi-agent reinforcement learning and sequenc...
人口快速老龄化、超大规模老年人口是中国式现代化面临的重要国情。当下,中国正面临人口老龄化加速发展期与实现中国式现代化过程叠加的发展新阶段,创造有利于经济高质量发展的人口条件,以及形成适应人口老龄化的经济发展新模式,是中国社会主义现代化发展的必由之路。因此,要以积极的态度看待人口老龄化带来的风险和挑战,挖掘老龄社会中存在的机遇,并主动应对人口老龄化问题,从根本上解决造成人口老龄化不断加速的难点、痛点...
In this talk, we discuss a unifying deep unfolding multi-sampling-ratio interpretable CS-MRI framework. The combined approach offers more generalizability than the existing deep-learning-based CS-MRI ...
Deep learning based methods have shown great potential for solving Vehicle Routing Problems (VRPs) in recent years. In the current learning based models, attention mechanism plays an important role an...
Passengers left behind is an important measure to describe the degree of congestion in metro systems. Note that passengers' left behind probabilities are different for their different tap-in times. Th...
We introduce the uncertainty of psychological motivation into a reciprocity model and explore its implications on behavior. More precisely, we assume that reciprocity sensitivities are subject to inco...
We focus on the nonconvex-strongly-convex bilevel optimization problem (BLO). In this BLO, the objective function of the upper-level problem is nonconvex and possibly nonsmooth, and the lower-level pr...
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...
Tensor-based modeling and computation emerge prominently with urgent demands from practical applications in the big data era. With the intrinsic sparsity in real data sets and the dimensionality reduc...
A matrix-based framework for the modeling, analysis and dynamics of Bayesian games are presented using the semi-tensor product of matrices. Static Bayesian games are considered first. A new conversion...

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