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

Fast algorithms for matrix multiplication, namely those that perform asymptotically fewer scalar operations than the classical algorithm, have been c…

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

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…

A general framework is developed to investigate the properties of useful choices of stationary spacelike slicings of stationary spacetimes whose cong…

We consider an intermediary's problem of dynamically matching demand and supply of heterogeneous types in a periodic-review fashion. More specificall…

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…

We focus on the downlink of a cellular system, which corresponds to the bulk of the data transfer in such wireless systems. We address the problem of…

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

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

We propose empirical dynamic programming algorithms for Markov decision processes (MDPs). In these algorithms, the exact expectation in the Bellman o…

In this paper we illustrate the simplifications produced by FDR in NNLO computations. We show with an explicit example that - due to its four-dimensi…

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

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