Intra-domain Consistency Enhancement for Unsupervised Person Re-identification

2021 ◽  
pp. 1-1
Author(s):  
Yaoyu Li ◽  
Hantao Yao ◽  
Changsheng Xu
Keyword(s):  
2013 ◽  
Vol 2013 ◽  
pp. 1-11 ◽  
Author(s):  
R. Company ◽  
L. Jódar ◽  
M. Fakharany ◽  
M.-C. Casabán

This paper deals with the numerical solution of option pricing stochastic volatility model described by a time-dependent, two-dimensional convection-diffusion reaction equation. Firstly, the mixed spatial derivative of the partial differential equation (PDE) is removed by means of the classical technique for reduction of second-order linear partial differential equations to canonical form. An explicit difference scheme with positive coefficients and only five-point computational stencil is constructed. The boundary conditions are adapted to the boundaries of the rhomboid transformed numerical domain. Consistency of the scheme with the PDE is shown and stepsize discretization conditions in order to guarantee stability are established. Illustrative numerical examples are included.


Author(s):  
Anna Louise D. Latour ◽  
Behrouz Babaki ◽  
Siegfried Nijssen

A number of data mining problems on probabilistic networks can be modeled as Stochastic Constraint Optimization and Satisfaction Problems, i.e., problems that involve objectives or constraints with a stochastic component. Earlier methods for solving these problems used Ordered Binary Decision Diagrams (OBDDs) to represent constraints on probability distributions, which were decomposed into sets of smaller constraints and solved by Constraint Programming (CP) or Mixed Integer Programming (MIP) solvers. For the specific case of monotonic distributions, we propose an alternative method: a new propagator for a global OBDD-based constraint. We show that this propagator is (sub-)linear in the size of the OBDD, and maintains domain consistency. We experimentally evaluate the effectiveness of this global constraint in comparison to existing decomposition-based approaches, and show how this propagator can be used in combination with another data mining specific constraint present in CP systems. As test cases we use problems from the data mining literature.


2002 ◽  
Vol 453 ◽  
pp. 315-344 ◽  
Author(s):  
REGHAN J. HILL ◽  
DONALD L. KOCH

The transition to unsteady flow and the dynamics of moderate-Reynolds-number flows in unbounded and wall-bounded periodic arrays of aligned cylinders are examined using lattice-Boltzmann simulations. The simulations are compared to experiments, which necessarily have bounding walls. With bounding walls, the transition to unsteady flow is accompanied by a loss of spatial periodicity, and the temporal fluctuations are chaotic at much smaller Reynolds numbers. The walls, therefore, affect the unsteady flows everywhere in the domain. Consistency between experiments and simulations is established by examining the wake lengths for steady flows and the fundamental frequencies at higher Reynolds numbers, both as a function of the Reynolds number. Simulations are used to examine the velocity fluctuations, flow topologies, and the fluctuating forces on the cylinders.


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