44 research outputs found
On the best choice of a damping sequence in iterative optimization methods
Some iterative methods of mathematical programming use a damping sequence {αt} such that 0 _< αt < 1 for all t, at - 0 as t - ∞, and Σαt = ∞. For example, αt = 1l(t + 1) in Brown's method for solving matrix games. In this paper, for a model class of iterative methods, the convergente rate for any damping sequence {αt}depending only on time t is computed. This computation is used to find the best damping sequence
Similarity classes of 3x3 matrices over a local principal ideal ring
In this paper similarity classes of three by three matrices over a local
principal ideal commutative ring are analyzed. When the residue field is
finite, a generating function for the number of similarity classes for all
finite quotients of the ring is computed explicitly.Comment: 14 pages, final version, to appear in Communications in Algebr
Monodromy of Cyclic Coverings of the Projective Line
We show that the image of the pure braid group under the monodromy action on
the homology of a cyclic covering of degree d of the projective line is an
arithmetic group provided the number of branch points is sufficiently large
compared to the degree.Comment: 47 pages (to appear in Inventiones Mathematicae
Proving The Ergodic Hypothesis for Billiards With Disjoint Cylindric Scatterers
In this paper we study the ergodic properties of mathematical billiards
describing the uniform motion of a point in a flat torus from which finitely
many, pairwise disjoint, tubular neighborhoods of translated subtori (the so
called cylindric scatterers) have been removed. We prove that every such system
is ergodic (actually, a Bernoulli flow), unless a simple geometric obstacle for
the ergodicity is present.Comment: 24 pages, AMS-TeX fil
Local Obfuscation Mechanisms for Hiding Probability Distributions
We introduce a formal model for the information leakage of probability
distributions and define a notion called distribution privacy as the local
differential privacy for probability distributions. Roughly, the distribution
privacy of a local obfuscation mechanism means that the attacker cannot
significantly gain any information on the distribution of the mechanism's input
by observing its output. Then we show that existing local mechanisms can hide
input distributions in terms of distribution privacy, while deteriorating the
utility by adding too much noise. For example, we prove that the Laplace
mechanism needs to add a large amount of noise proportionally to the infinite
Wasserstein distance between the two distributions we want to make
indistinguishable. To improve the tradeoff between distribution privacy and
utility, we introduce a local obfuscation mechanism, called a tupling
mechanism, that adds random dummy data to the output. Then we apply this
mechanism to the protection of user attributes in location based services. By
experiments, we demonstrate that the tupling mechanism outperforms popular
local mechanisms in terms of attribute obfuscation and service quality.Comment: Full version of Proc. ESORICS 2019 (with a longer appendix
On the best choice of a damping sequence in iterative optimization methods
Some iterative methods of mathematical programming use a damping sequence {αt} such that 0 _< αt < 1 for all t, at - 0 as t - ∞, and Σαt = ∞. For example, αt = 1l(t + 1) in Brown's method for solving matrix games. In this paper, for a model class of iterative methods, the convergente rate for any damping sequence {αt}depending only on time t is computed. This computation is used to find the best damping sequence