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The Gaussian random walk, sampling Brownian motion, and the Riemann zeta function

Johan van Leeuwaarden (Eindhoven University of Technology, EURANDOM, NYU)

We consider the Gaussian random walk (one-dimensional random walk with normally distributed increments), and in particular the moments of its maximum M. Explicit expressions for all moments of M are derived in terms of Taylor series with coefficients that involve the Riemann zeta function. We build upon the work of Chang and Peres (1997) on P(M=0) and Bateman's formulas on Lerch's transcendent. Our result for E(M) completes earlier work of Kingman (1965), Siegmund (1985), and Chang and Peres (1997). The…

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Convergence of unitary matrix integrals

Benoît Collins (University of Ottawa)

We introduce the unitary Schwinger-Dyson equation associated to a selfadjoint polynomial potential V. The V=0 case corresponds to the free product state, so the Schwinger-Dyson equation can be considered as a deformation of free probability. We show that the solutions of this equation are unique for small V's and correspond to a large N limit of a multi-matrix model. This technique allows to show that a wide class of unitary and orthogonal multi-matrix models converge asymptotically. We also give a…

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Sequential algorithms for generating random graphs

Mohsen Bayati (Microsoft Research New England)

Large-scale complex networks have been the objects of study for the past two decades, and one central problem have been constructing or designing realistic models for such networks. This problem appears in a variety of applications including coding theory and systems biology. Unfortunately, the existing algorithms for this problem have large running times, making them impractical to use for networks with millions of links. We will present a technique to design an almost linear time algorithm for generating random graphs…

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A New Look at the Compound Poisson Distribution and Compound Poisson Approximation using Entropy

Mokshay Madiman (Yale University)

We develop an information-theoretic foundation for compound Poisson approximation and limit theorems (analogous to the corresponding developments for the central limit theorem and for simple Poisson approximation). First, su?cient conditions are given under which the compound Poisson distribution has maximal entropy within a natural class of probability measures on the nonnegative integers. In particular, it is shown that a maximum entropy property is valid if the measures under consideration are log-concave, but that it fails in general. Second, approximation bounds…

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Fractional simple random walk

Scott Sheffield (MIT Math)

Fractional Brownian motions are the most natural generalizations of ordinary (one-dimensional) Brownian motions that allow for some amount of long range dependence (a.k.a. "momentum effects"). They are sometimes used in mathematical finance as models for logarithmic asset prices. We describe some natural random simple walks on the integers that have fractional Brownian motion as a scaling limit. In a sense, these walks are the most natural discrete analogs of fractional Brownian motion.

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The Smoothed Linear Program for Approximate Dynamic Programming

Vivek F. Farias (MIT Sloan)

We present a novel linear program for the approximation of the dynamic programming value function in high-dimensional stochastic control problems. LP approaches to approximate DP naturally restrict attention to approximations that, depending on the context, are upper or lower bounds to the optimal value function. Our program -- the `smoothed LP' -- relaxes this restriction in an appropriate fashion while remaining computationally tractable. Doing so appears to have several advantages: o We demonstrate superior bounds on the quality of approximation…

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On Resolution, Sparse Signal Recovery, and Random Access Communication

Vivek Goyal (MIT EECS)

Resolution of a data acquisition system is usually thought to be determined completely by sensing properties, such as density and accuracy of measurements. This talk advocates the view that resolution is, in addition, dependent on signal modeling and the complexity of computations allowed. This view is developed concretely for the acquisition of sparse signals, where the asymptotic relationship between resolution and the number of measurements is studied for algorithms with various complexities. The sparse signal recovery problem corresponds perfectly to…

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Asymptotics for preferential attachment random graphs via Stein’s method

Erol Peköz (Boston University)

Preferential attachment random graphs evolve in time by sequentially adding vertices and edges randomly so that connections to vertices having high degree are favored. There has been an explosion of research on these models since Barabasi and Albert popularized them in 1999 to explain the so-called power law behavior observed in real networks such as the graph of the Internet where Web pages correspond to vertices and hyperlinks between them correspond to edges. In this talk we will show how…

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Does god play dice? An I/O scheduling and airplane boarding perspective

Eitan Bachmat (Ben-Gurion University)

Given N I/O requests to a disk drive, how long will it take the disk drive to service them? How long does it take to board an airplane? We will show that such questions are modeled by the same math that models the universe in relativity theory, namely, space-time (Lorentzian) geometry.As a result of this connection we will try to understand what is the best way to service I/O, what is the best airplane boarding policy and what makes free…

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Delay optimality in switched networks

Yuan Zhong (MIT ORC)

We consider a switched (queueing) network in which there are constraints on which queues may be served simultaneously; such networks have been used to effectively model input-queued switches and wireless networks. The scheduling policy for such a network specifies which queues to serve at any point in time, based on the current state or past history of the system. In the main result, we provide a new class of online scheduling policies that achieve optimal average queue-size scaling for a…

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