Mobile communication is nowadays taken for granted. Having started primarily as a service for speech communication, data service and mobile Internet access are now driving the evolution of network infrastructure. Operators are facing the challenge to match the demand by continuously expanding and upgrading the network infrastructure. However, the evolution of the customer’s demand is uncertain....

We present a new stochastic learning machine for speech separation based on the variational recurrent neural network (VRNN). This VRNN is constructed from the perspectives of generative stochastic network and variational auto-encoder. The idea is to faithfully characterize the randomness of hidden state of a recurrent neural network through variational learning. The neural parameters under this...

We examine the dynamic formation and stochastic evolution of networks connecting individuals. The payoff to an individual from an economic or social activity depends on the network of connections among individuals. Over time individuals form and sever links connecting themselves to other individuals based on the improvement that the resulting network offers them relative to the current network....

In this paper we propose a composite Variational Inequality formulation for modeling multi-mode, multi-class and multi-criteria stochastic dynamic user equilibrium problem in recurrent congestion network with queues. The each mode of travelers is classified into two classes. One is the equipped traveler following stochastic dynamic user-equilibrium with less uncertainty of travel cost, another ...

A multistage stochastic programming approach to airline network revenue management is presented. The objective is to determine seat protection levels for all itineraries, fare classes, point of sales of the airline network and all data collection points of the booking horizon such that the expected revenue is maximized. While the passenger demand and cancelation rate processes are the stochasti...

We describe a stochastic network interdiction model for locating sensors that detect nuclear material. A nuclear material smuggler selects a path through a transportation network that maximizes the probability of avoiding detection. An interdictor installs sensors to minimize that maximum probability. We formulate this problem as a bi-level stochastic mixed-integer program, and then focus on a ...

We model the formation of friendships as repeated cooperation within a set of heterogeneous players. The model is built around three of the most important facts about friendship: friends help each other, there is reciprocity in the relationship and people usually have only a few friends. In our results, we explain how similarity between people affects the friendship selection. We also character...

This paper considers a stylized model of network formation in which relations among agents are subject to frictions, as described in Bala and Goyal [A non cooperative model of network formation, Econometrica 68 (2000) 1181–1231]. We analyze the process of network formation in a dynamic framework where selfinterested individuals can form or delete links and, occasionally, make mistakes. Then, us...

Experimental data suggest that neural circuits configure their synaptic connectivity for a given computational task. They also point to dopamine-gated stochastic spine dynamics as an important underlying mechanism, and they show that the stochastic component of synaptic plasticity is surprisingly strong. We propose a model that elucidates how task-dependent self-configuration of neural circuits...

Recently some stochastic (probabilistic) extensions of the deterministic network calculus have been developed, mainly for exploiting the statistical multiplexing of flows aggregated in packet based communication networks. This exploitation could result ”better” stochastic performance bounds than those bounds provided by the inherently worst case analysis of the deterministic network calculus. T...