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Vsevolod Shneer

Publications and source records attributed to Vsevolod Shneer.

6 recordsLinked to original sources

Broadcasting on Random Trees: Martingale Methods and Error Bounds

The broadcasting problem on trees concerns the transmission of binary information along the edges of a tree. In the formulation studied here, each vertex carries one of two colours, and along every edge the colour is transmitted with error probability $q$. The central question is whether the root colour can be reconstructed from the observed colours of all vertices in the tree, but crucially, without knowing which vertex is the root. We study the problem of reconstructing the root colour in a broadcasting process on random trees, focusing on the majority rule estimator. We introduce a novel and adaptable martingale approach for analysing the colour imbalance. This method provides a simpler and more powerful alternative to existing techniques. Our martingale approach unifies the analysis of the different tree models and leads to linear upper bounds for the error probability of the majority rule estimator in each case. This shows that, for a broad class of random tree models, the error probability of the majority rule admits a linear upper bound in $q$.

math.PR

Migration-Contagion Processes

Consider a migration process based on a closed network of N stations with K_N customers. Each station is a ./M/\infty queue with service (migration) rate mu. Upon departure, a customer is routed at random to another station. In addition to migration, these customers are subject to an SIS (Susceptible, Infected, Susceptible) dynamics: customers are either I for infected, or S for susceptible. They can swap their state either from I to S or from S to I only in stations. At any station, each S customer becomes I with rate alpha Y if there are Y infected customers in the station, and each I customer recovers and becomes S with rate beta. We let N tend to infinity and assume that lim_{N\to infty} K_N/N= eta>0. The main problem is about the set of parameters for which there exists a stationary regime where the epidemic survives in the thermodynamic limit. We establish several structural properties of the system, which allow us to give the phase transition diagram of this thermodynamic limit w.r.t. eta. The analysis of the SIS model reduces to that of a wave-type PDE for which we found no explicit solution. This SIS model is one among several companion stochastic processes with migration and contagion. Two of them are discussed as they provide some bounds and approximations to SIS. These two variants are the DOCS (Departure On Change of State) and the AIR (Averaged Infection Rate), which both admit closed-form solutions. The AIR system is a mean-field model where the infection mechanism is based on the empirical average of the number of infected customers in all stations. The latter admits a product-form solution. DOCS features accelerated migration in that each change of SIS state implies an immediate departure. It leads to another wave-type PDE that admits a closed-form solution.

math.PR

Stochastic Stability of Monotone Economies in Regenerative Environments

We introduce and analyze a new class of monotone stochastic recursions in a regenerative environment which is essentially broader than that of Markov chains. We prove stability theorems and apply our results {to three canonical models in recursive economics}, generalizing some known stability results to the cases when driving sequences are not independent and identically distributed.

math.PR

Structural bias in population-based algorithms

Challenging optimisation problems are abundant in all areas of science. Since the 1950s, scientists have developed ever-diversifying families of black box optimisation algorithms designed to address any optimisation problem, requiring only that quality of a candidate solution is calculated via a fitness function specific to the problem. For such algorithms to be successful, at least three properties are required: an effective informed sampling strategy, that guides generation of new candidates on the basis of fitnesses and locations of previously visited candidates; mechanisms to ensure efficiency, so that same candidates are not repeatedly visited; absence of structural bias, which, if present, would predispose the algorithm towards limiting its search to some regions of solution space. The first two of these properties have been extensively investigated, however the third is little understood. In this article we provide theoretical and empirical analyses that contribute to the understanding of structural bias. We prove a theorem concerning dynamics of population variance in the case of real-valued search spaces. This reveals how structural bias can manifest as non-uniform clustering of population over time. Theory predicts that structural bias is exacerbated with increasing population size and problem difficulty. These predictions reveal two previously unrecognised aspects of structural bias. Respectively, increasing population size, though ostensibly promoting diversity, will magnify any inherent structural bias, and effects of structural bias are more apparent when faced with difficult problems. Our theoretical result also suggests that two commonly used approaches to enhancing exploration, increasing population size and increasing disruptiveness of search operators, have quite distinct implications in terms of structural bias.

cs.NE

A Random Multiple Access Protocol with Spatial Interactions

We analyse an ALOHA-type random multiple-access protocol where users have local interactions. We show that the fluid model of the system workload satisfies a certain differential equation. We obtain a sufficient condition for the stability of this differential equation and deduce from that a sufficient condition for the stability of the protocol. We discuss the necessary condition. Further, for the underlying Markov chain, we estimate the rate of convergence to the stationary distribution. Then we establish an interesting and unexpected result showing that the main diagonal is locally unstable if the input rate is sufficiently small. Finally, we consider two generalisations of the model.

math.PR

Asymptotics for first-passage times of Lévy processes and random walks

We study the exact asymptotics for the distribution of the first time $τ_x$ a Lévy process $X_t$ crosses a negative level $-x$. We prove that $\mathbf P(τ_x>t)\sim V(x)\mathbf P(X_t\ge 0)/t$ as $t\to\infty$ for a certain function $V(x)$. Using known results for the large deviations of random walks we obtain asymptotics for $\mathbf P(τ_x>t)$ explicitly in both light and heavy tailed cases. We also apply our results to find asymptotics for the distribution of the busy period in an M/G/1 queue.

math.PR