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We study time-uniform statistical inference for parameters in stochastic approximation (SA), which encompasses a bunch of applications in optimization and machine learning. To that end, we analyze the almost-sure convergence rates of the…

Machine Learning · Statistics 2024-10-22 Chuhan Xie , Kaicheng Jin , Jiadong Liang , Zhihua Zhang

This paper presents a stochastic algorithm for iterative error control decoding. We show that the stochastic decoding algorithm is an approximation of the sum-product algorithm. When the code's factor graph is a tree, as with trellises, the…

Information Theory · Computer Science 2007-07-13 Chris Winstead , Anthony Rapley , Vincent C. Gaudet , Christian Schlegel

The fundamental question considered in algorithms on strings is that of indexing, that is, preprocessing a given string for specific queries. By now we have a number of efficient solutions for this problem when the queries ask for an exact…

Data Structures and Algorithms · Computer Science 2023-04-04 Paweł Gawrychowski , Garance Gourdel , Tatiana Starikovskaya , Teresa Anna Steiner

Sharpe ratio is widely used in asset management to compare and benchmark funds and asset managers. It computes the ratio of the excess return over the strategy standard deviation. However, the elements to compute the Sharpe ratio, namely,…

Statistical Finance · Quantitative Finance 2019-05-15 Eric Benhamou

The cornerstone of any algorithm computing all repetitions in a string of length n in O(n) time is the fact that the number of runs (or maximal repetitions) is O(n). We give a simple proof of this result. As a consequence of our approach,…

Data Structures and Algorithms · Computer Science 2008-02-21 Maxime Crochemore , Lucian Ilie

We introduce an statistical mechanical formalism for the study of discrete-time stochastic processes with which we prove: (i) General properties of extremal chains, including triviality on the tail $\sigma$-algebra, short-range…

Probability · Mathematics 2007-05-23 Roberto Fernandez , Gregory Maillard

Bounds of the accuracy of the normal approximation to the distribution of a sum of independent random variables are improved under relaxed moment conditions, in particular, under the absence of moments of orders higher than the second.…

Probability · Mathematics 2015-07-06 V. Yu. Korolev , A. V. Dorofeeva

Consensus problems for strings and sequences appear in numerous application contexts, ranging from bioinformatics over data mining to machine learning. Closing some gaps in the literature, we show that several fundamental problems in this…

Discrete Mathematics · Computer Science 2019-04-12 Laurent Bulteau , Vincent Froese , Rolf Niedermeier

For a large class of quickly mixing dynamical systems, we prove that the error in the almost sure approximation with a Brownian motion is of order O((log n)^a) with a $\ge$ 2. Specifically, we consider nonuniformly expanding maps with…

Probability · Mathematics 2018-11-26 C Cuny , J Dedecker , A Korepanov , Florence Merlevède

There is a random variable (X) with a determined outcome (i.e., X = x0), p(x0) = 1. Consider x0 to have a discrete uniform distribution over the integer interval [1, s], where the size of the sample space (s) = 1, in the initial state, such…

Statistical Finance · Quantitative Finance 2021-06-01 Laurence F Lacey

Strict frequentism defines probability as the limiting relative frequency in an infinite sequence. What if the limit does not exist? We present a broader theory, which is applicable also to random phenomena that exhibit diverging relative…

Statistics Theory · Mathematics 2023-06-07 Christian Fröhlich , Rabanus Derr , Robert C. Williamson

For a spectrally positive strictly stable process with index in (1,2), the paper obtains i) the density of the time when the process makes first exit from an interval by hitting the interval's lower end point before jumping over its upper…

Probability · Mathematics 2018-06-21 Zhiyi Chi

Using the superstatistics method, we propose an extension of the random matrix theory to cover systems with mixed regular-chaotic dynamics. Unlike most of the other works in this direction, the ensembles of the proposed approach are basis…

Statistical Mechanics · Physics 2007-05-23 A. Y. Abul-Magd

Scientific explanation often requires inferring maximally predictive features from a given data set. Unfortunately, the collection of minimal maximally predictive features for most stochastic processes is uncountably infinite. In such…

Statistical Mechanics · Physics 2017-05-31 Sarah E. Marzen , James P. Crutchfield

The high-energy limit of stringy symmetries, derived from the decoupling of two types of zero-norm states in the old covariant first quantized (OCFQ) spectrum of open bosonic string, are used to reproduce Gross's linear relations among…

High Energy Physics - Theory · Physics 2007-05-23 Jen-Chi Lee

We identify string corrections to the EM memory effect. Though largely negligible in the low-energy limit, the effect become relevant in high-energy collisions and in extreme events. We illustrate our findings in a simple unoriented bosonic…

High Energy Physics - Theory · Physics 2021-02-03 Alice Aldi , Massimo Bianchi , Maurizio Firrotta

Consider two independent random strings having same length and taking values uniformly in a common finite alphabet. We study the order of the variance of the length of the longest common subsequences (LCS) of these strings when long blocks,…

Probability · Mathematics 2016-09-26 S. Amsalu , C. Houdré , H. Matzinger

This paper is devoted to the error analysis of a time-spectral algorithm for fractional diffusion problems of order $\alpha$ ($0 < \alpha < 1$). The solution regularity in the Sobolev space is revisited, and new regularity results in the…

Numerical Analysis · Mathematics 2021-06-08 Hao Luo , Xiaoping Xie

Stochastic approximation algorithm is a useful technique which has been exploited successfully in probability theory and statistics for a long time. The step sizes used in stochastic approximation are generally taken to be deterministic and…

Probability · Mathematics 2019-09-25 Ujan Gangopadhyay , Krishanu Maulik

A statistical model of discrete finite length random processes with negative power law spectral densities is presented. The definition of terms is followed by a description of the spectral density trend. An algorithmic construction of…

Instrumentation and Methods for Astrophysics · Physics 2023-02-13 Robert Kimberk , Keara Carter , Todd Hunter
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