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Communication compression is an essential strategy for alleviating communication overhead by reducing the volume of information exchanged between computing nodes in large-scale distributed stochastic ...
In this talk I will talk about our recent work on the three dimensional stochastic Navier-Stokes equations via convex integration method. First we establish non-uniqueness in law, existence and non-un...
作为一项极其复杂的系统工程,飞行器的研制总会受到制造误差、飞行状态等诸多不确定性因素的影响,如果这些不确定性因素在设计过程中被忽视,很可能会导致飞行器整体性能急剧变差,甚至造成致命性的灾难。因此,近年来飞行器的不确定性研究方法和手段在航空航天领域得到了广泛应用,NASA早在2002年就开始着手规划考虑不确定性因素影响的研究工作,AIAAASME每年都举办关于不确定性研究的专题研讨会。当前我国各型...
作为一项极其复杂的系统工程,飞行器的研制总会受到制造误差、飞行状态等诸多不确定性因素的影响,如果这些不确定性因素在设计过程中被忽视,很可能会导致飞行器整体性能急剧变差,甚至造成致命性的灾难。因此,近年来飞行器的不确定性研究方法和手段在航空航天领域得到了广泛应用,NASA早在2002年就开始着手规划考虑不确定性因素影响的研究工作,AIAAASME每年都举办关于不确定性研究的专题研讨会。当前我国各型...
2018年3月20日,控制领域国际顶级期刊《Automatica》刊发了中国地质大学自动化学院宗小峰教授的“随机系统稳定性方面新成果”--Stability of stochastic functional differential systems using degenerate Lyapunov functionals and applications。
A generic and practical methodology is presented for 3D surface mesh reconstruction from the terrestrial laser scanner (TLS) derived point clouds. It has two main steps. The first step deals with deve...
IUTAM Symposium on Stochastic dynamical systems approaches to fluid flow transitions.
The Healthcare Critical Infrastructure (HCI) protects all sectors of the society from hazards such as terrorism, infectious disease outbreaks, and natural disasters. HCI plays a significant role in re...
We formulate the loop-free binary superoptimization task as a stochastic search problem. The competing constraints of transformation correctness and performance improvement are encoded as terms in a c...
The aggressive optimization of floating-point computations is an important problem in high-performance computing. Unfortunately,floating-point instruction sets have complicated semantics that often fo...
The optimization of short sequences of loop-free, fixed-point assembly code sequences is an important problem in highperformance computing. However, the competing constraints of transformation correct...
We study several stochastic combinatorial problems, includ-ing the expected utility maximization problem, the stochas-tic knapsack problem and the stochastic bin packing prob-lem. A common technical c...
In this paper, we investigate the power of online learning in stochastic network optimization with unknown system statistics a priori. We are interested in understanding how information and learning c...
We consider the stochastic geometry model where the location of each node is a random point in a given metric space,or the existence of each node is uncertain. We study the problem-s of computing the ...
In this paper, we develop the Receding Learning-aided Control algorithm ( RLC ) for solving optimization problems in general stochastic networks with potentially non-stationary system dynamics. RLC is...

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