With the rapid development of urbanization, metro becomes more and important for people’s travel in big cities. To quantitatively describe passenger flows on congested transfer routes, this paper introduces a dynamic model based automated data from automatic fare collection (AFC) vehicle location (AVL) systems. An expectation maximization (EM) algorithm is proposed to compute maximum likelihood...

We consider off-line vector assignment problems. The goal is to assign input vectors to machines so that a given target function is minimized. The target function usually gives some measure of the quality of distribution of input vectors among machines. We deal with an asymmetric setting where the cost functions per machine may be different for different machines, and design a PTAS for a wide c...

Markov state models (MSMs) have become one of the preferred methods for analysis and interpretation molecular dynamics (MD) simulations conformational transitions in biopolymers. While there is great variation terms implementation, a well-defined workflow involving multiple steps often adopted. Typically, coordinates are first subjected to dimensionality reduction then clustered into small “mic...

This paper studies a deep learning approach for binary assignment problems in wireless networks, which identifies variables permutation matrices. poses challenges designing structure of neural network and its training strategies generating feasible solutions. To this end, develop new Sinkhorn learns non-convex projection task onto set An unsupervised algorithm is proposed where the can be appli...

Fluid simulation is a common challenge in computer graphics, and one that illustrates the need for efficient physical models. While physically accurate simulations of fluid dynamics can be conducted by solving the Navier-Stokes equations exactly, this is computationally expensive in general, and as such is often not suitable for graphics applications, especially those that are meant to run in r...