1,186 research outputs found
Verifying proofs in constant depth
In this paper we initiate the study of proof systems where verification of proofs proceeds by NC circuits. We investigate the question which languages admit proof systems in this very restricted model. Formulated alternatively, we ask which languages can be enumerated by NC functions. Our results show that the answer to this problem is not determined by the complexity of the language. On the one hand, we construct NC proof systems for a variety of languages ranging from regular to NP-complete. On the other hand, we show by combinatorial methods that even easy regular languages such as Exact-OR do not admit NC proof systems. We also present a general construction of proof systems for regular languages with strongly connected NFA's
Alleyne on the Ground: Factfinding that Limits Eligibility for Probation or Parole Release
This article addresses the impact of Alleyne v. United States on statutes that restrict an offender’s eligibility for release on parole or probation. Alleyne is the latest of several Supreme Court decisions applying the rule announced in the Court’s 2000 ruling, Apprendi v. New Jersey. To apply Alleyne, courts must for the first time determine what constitutes a minimum sentence and when that minimum is mandatory. These questions have proven particularly challenging in states that authorize indeterminate sentences, when statutes that delay the timing of eligibility for release are keyed to judicial findings at sentencing. The same questions also arise, in both determinate and indeterminate sentencing jurisdictions, under statutes that limit the option of imposing either probation or a suspended sentence upon judicial fact finding. In this Article, we argue that Alleyne invalidates such statutes. We provide analyses that litigants and judges might find useful as these Alleyne challenges make their way through the courts, and offer a menu of options for state lawmakers who would prefer to amend their sentencing law proactively in order to minimize disruption of their criminal justice systems
Controlled Data Sharing for Collaborative Predictive Blacklisting
Although sharing data across organizations is often advocated as a promising
way to enhance cybersecurity, collaborative initiatives are rarely put into
practice owing to confidentiality, trust, and liability challenges. In this
paper, we investigate whether collaborative threat mitigation can be realized
via a controlled data sharing approach, whereby organizations make informed
decisions as to whether or not, and how much, to share. Using appropriate
cryptographic tools, entities can estimate the benefits of collaboration and
agree on what to share in a privacy-preserving way, without having to disclose
their datasets. We focus on collaborative predictive blacklisting, i.e.,
forecasting attack sources based on one's logs and those contributed by other
organizations. We study the impact of different sharing strategies by
experimenting on a real-world dataset of two billion suspicious IP addresses
collected from Dshield over two months. We find that controlled data sharing
yields up to 105% accuracy improvement on average, while also reducing the
false positive rate.Comment: A preliminary version of this paper appears in DIMVA 2015. This is
the full version. arXiv admin note: substantial text overlap with
arXiv:1403.212
First exit times of solutions of stochastic differential equations driven by multiplicative Levy noise with heavy tails
In this paper we study first exit times from a bounded domain of a gradient
dynamical system perturbed by a small multiplicative
L\'evy noise with heavy tails. A special attention is paid to the way the
multiplicative noise is introduced. In particular we determine the asymptotics
of the first exit time of solutions of It\^o, Stratonovich and Marcus canonical
SDEs.Comment: 19 pages, 2 figure
Lognormal scale invariant random measures
In this article, we consider the continuous analog of the celebrated
Mandelbrot star equation with lognormal weights. Mandelbrot introduced this
equation to characterize the law of multiplicative cascades. We show existence
and uniqueness of measures satisfying the aforementioned continuous equation;
these measures fall under the scope of the Gaussian multiplicative chaos theory
developed by J.P. Kahane in 1985 (or possibly extensions of this theory). As a
by product, we also obtain an explicit characterization of the covariance
structure of these measures. We also prove that qualitative properties such as
long-range independence or isotropy can be read off the equation.Comment: 31 pages; Probability Theory and Related Fields (2012) electronic
versio
L\'evy-Schr\"odinger wave packets
We analyze the time--dependent solutions of the pseudo--differential
L\'evy--Schr\"odinger wave equation in the free case, and we compare them with
the associated L\'evy processes. We list the principal laws used to describe
the time evolutions of both the L\'evy process densities, and the
L\'evy--Schr\"odinger wave packets. To have self--adjoint generators and
unitary evolutions we will consider only absolutely continuous, infinitely
divisible L\'evy noises with laws symmetric under change of sign of the
independent variable. We then show several examples of the characteristic
behavior of the L\'evy--Schr\"odinger wave packets, and in particular of the
bi-modality arising in their evolutions: a feature at variance with the typical
diffusive uni--modality of both the L\'evy process densities, and the usual
Schr\"odinger wave functions.Comment: 41 pages, 13 figures; paper substantially shortened, while keeping
intact examples and results; changed format from "report" to "article";
eliminated Appendices B, C, F (old names); shifted Chapters 4 and 5 (old
numbers) from text to Appendices C, D (new names); introduced connection
between Relativistic q.m. laws and Generalized Hyperbolic law
Controllability and Qualitative properties of the solutions to SPDEs driven by boundary L\'evy noise
Let be the solution to the following stochastic evolution equation (1)
du(t,x)& = &A u(t,x) dt + B \sigma(u(t,x)) dL(t),\quad t>0; u(0,x) = x taking
values in an Hilbert space \HH, where is a \RR valued L\'evy process,
an infinitesimal generator of a strongly continuous semigroup,
\sigma:H\to \RR bounded from below and Lipschitz continuous, and B:\RR\to H
a possible unbounded operator. A typical example of such an equation is a
stochastic Partial differential equation with boundary L\'evy noise. Let
\CP=(\CP_t)_{t\ge 0} %{\CP_t:0\le t<\infty}T>0BAx\in H\CP_T^\star \delta_xH\HHLAB$ the solution of Equation [1] is
asymptotically strong Feller, respective, has a unique invariant measure. We
apply these results to the damped wave equation driven by L\'evy boundary
noise
The weakly coupled fractional one-dimensional Schr\"{o}dinger operator with index
We study fundamental properties of the fractional, one-dimensional Weyl
operator densely defined on the Hilbert space
and determine the asymptotic behaviour of
both the free Green's function and its variation with respect to energy for
bound states. In the sequel we specify the Birman-Schwinger representation for
the Schr\"{o}dinger operator
and extract the finite-rank portion which is essential for the asymptotic
expansion of the ground state. Finally, we determine necessary and sufficient
conditions for there to be a bound state for small coupling constant .Comment: 16 pages, 1 figur
Regularity of Ornstein-Uhlenbeck processes driven by a L{\'e}vy white noise
The paper is concerned with spatial and time regularity of solutions to
linear stochastic evolution equation perturbed by L\'evy white noise "obtained
by subordination of a Gaussian white noise". Sufficient conditions for spatial
continuity are derived. It is also shown that solutions do not have in general
\cadlag modifications. General results are applied to equations with fractional
Laplacian. Applications to Burgers stochastic equations are considered as well.Comment: This is an updated version of the same paper. In fact, it has already
been publishe
Mixtures in non stable Levy processes
We analyze the Levy processes produced by means of two interconnected classes
of non stable, infinitely divisible distribution: the Variance Gamma and the
Student laws. While the Variance Gamma family is closed under convolution, the
Student one is not: this makes its time evolution more complicated. We prove
that -- at least for one particular type of Student processes suggested by
recent empirical results, and for integral times -- the distribution of the
process is a mixture of other types of Student distributions, randomized by
means of a new probability distribution. The mixture is such that along the
time the asymptotic behavior of the probability density functions always
coincide with that of the generating Student law. We put forward the conjecture
that this can be a general feature of the Student processes. We finally analyze
the Ornstein--Uhlenbeck process driven by our Levy noises and show a few
simulation of it.Comment: 28 pages, 3 figures, to be published in J. Phys. A: Math. Ge
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