Concept

Concentration inequality

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On the Capacity of a Code Division Multiple Access System

Nicolas Macris, Satish Babu Korada

We consider multiuser communication on a binary input additive white Gaussian noise channel using Randomly Spread-Code Division Multiple Access. We show concentration of various quantities of the system including the capacity and the free energy. We also o ...

2007

Gossip along the way: order-optimal consensus through randomized path averaging

Martin Vetterli, Patrick Thiran, Florence Bénézit

Gossip algorithms have recently received significant attention, mainly because they constitute simple and robust algorithms for distributed information processing over networks. However for many topologies that are realistic for wireless ad-hoc and sensor ...

2007

Capacity upper bounds for the deletion channel

Suhas Diggavi, Henry Pfister

We present two upper bounds on the capacity of the i.i.d. binary deletion channel, where each bit is independently deleted with a fixed probability d. The first can be numerically evaluated for any fixed d. The second provides an asymptotic upper bound as ...

Ieee Service Center, 445 Hoes Lane, Po Box 1331, Piscataway, Nj 08855-1331 Usa2007

Randomization bounds on Gaussian arbitrarily varying channels

Michael Christoph Gastpar

The random coding capacity of the Gaussian arbitrarily varying channel (GAVC) under a maximal probability of error criterion is equal to that of an additive white Gaussian noise (AWGN) channel with the interference power as additional noise. The determinis ...

Ieee Service Center, 445 Hoes Lane, Po Box 1331, Piscataway, Nj 08855-1331 Usa2006

Probabilistic observers for a class of uncertain biological processes

Benoît Chachuat, Olivier Bernard

In this paper, probabilistic observers are considered for a class of continuous biological processes described by mass-balance-based models. It is assumed that the probability density functions (PDFs) of the uncertain parameters and inputs of the model, as ...

2006

Worst-Case Bounds for Gaussian Process Models

Matthias Seeger

We present a competitive analysis of some non-parametric Bayesian algorithms in a worst-case online learning setting, where no probabilistic assumptions about the generation of the data are made. We consider models which use a Gaussian process prior (over ...

2006

The Heard-Of Model: Unifying all Benign Failures

André Schiper

Problems in fault-tolerant distributed computing have been studied in a variety of models. These models are structured around two central ideas: 1. Degree of synchrony and failure model are two independent parameters that determine a particular type of sys ...

2006

Estimating the Confidence Interval of Expected Performance Curve in Biometric Authentication Using Joint Bootstrap

Samy Bengio, Norman Hoon Thian Poh

Evaluating biometric authentication performance is a complex task because the performance depends on the user set size, composition and the choice of samples. We propose to reduce the performance dependency of these three factors by deriving appropriate co ...

IDIAP2006

On the capacity of large Gaussian relay networks

Martin Vetterli, Michael Christoph Gastpar

The capacity of a particular large Gaussian relay network is determined in the limit as the number of relays tends to infinity. Upper bounds are derived from cut-set arguments, and lower bounds follow from an argument involving uncoded transmission. It is ...

Institute of Electrical and Electronics Engineers2005

Generalized Bounds for Convex Multistage Stochastic Programs

Daniel Kuhn

This book investigates convex multistage stochastic programs whose objective and constraint functions exhibit a generalized nonconvex dependence on the random parameters. Although the classical Jensen and Edmundson-Madansky type bounds or their extensions ...

Springer-Verlag2005