We consider the multidimensional generalised stochastic Burgers equation in the space-periodic setting: $ \partial \mathbf{u}/\partial t+$ $(\nabla…

Motivated by the broadcast view of the interference channel, the new problem of communication with disturbance constraints is formulated. The rate-di…

The varying-coefficient model is an important nonparametric statistical model that allows us to examine how the effects of covariates vary with expos…

We initiate the study of efficient mechanism design with guaranteed good properties even when players participate in multiple different mechanisms si…

Heterogeneity is often natural in many contemporary applications involving massive data. While posing new challenges to effective learning, it can pl…

This article provides a Wilsonian description of the perturbatively renormalizable Tensorial Group Field Theory introduced in arXiv:1303.6772 [hep-th…

For the large-scale linear discrete ill-posed problem $\min\|Ax-b\|$ or $Ax=b$ with $b$ contaminated by a white noise, Lanczos bidiagonalization base…

In this paper, we show how the problem of designing optimal $H_\infty$ state-feedback controllers for distributed-parameter systems can be formulated…

Biased stochastic estimators, such as finite-differences for noisy gradient estimation, often contain parameters that need to be properly chosen to b…

We present an analysis of wave propagation in a two step-index, parallel waveguide system. The goal is to quantify the effect of scattering at random…

We introduce a very general method for high-dimensional classification, based on careful combination of the results of applying an arbitrary base cla…

Any performance analysis based on stochastic simulation is subject to the errors inherent in misspecifying the modeling assumptions, particularly the…

A classical problem in matrix computations is the efficient and reliable approximation of a given matrix by a matrix of lower rank. The truncated sin…

This paper considers constrained optimization over a renewal system. A controller observes a random event at the beginning of each renewal frame and …

A fully discrete approximation of the semi-linear stochastic wave equation driven by multiplicative noise is presented. A standard linear finite elem…

Predictive analytics is increasingly used to guide decision-making in many applications. However, in practice, we often have limited data on the true…

We study the problem of learning \emph{across} a sequence of price experiments for related products, focusing on implementing the Thompson sampling a…

We introduce a new approach for designing numerical schemes for stochastic differential equations (SDEs). The approach, which we have called directio…

We study web and mobile applications that are used to schedule advance service, from medical appointments to restaurant reservations. We model them a…

The Kuramoto model of a system of coupled phase oscillators and its many variations are frequently used to describe synchronization phenomena in natu…

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