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The lefthanded Lov\'asz local lemma (LLLL) is a generalization of the Lov\'asz local lemma (LLL), a powerful technique from the probabilistic method. We prove a computable version of the LLLL and use it to effectivize a collection of…

Logic · Mathematics 2024-06-19 Daniel Mourad

This paper develops several average-case reduction techniques to show new hardness results for three central high-dimensional statistics problems, implying a statistical-computational gap induced by robustness, a detection-recovery gap and…

Computational Complexity · Computer Science 2020-05-20 Matthew Brennan , Guy Bresler

In recent decades, a number of profound theorems concerning approximation of hard counting problems have appeared. These include estimation of the permanent, estimating the volume of a convex polyhedron, and counting (approximately) the…

Data Structures and Algorithms · Computer Science 2020-09-07 Isabel Beichl , Alathea Jensen

We deal with the random combinatorial structures called assemblies. By weakening the logarithmic condition which assures regularity of the number of components of a given order, we extend the notion of logarithmic assemblies. Using the…

Probability · Mathematics 2009-03-06 Eugenijus Manstavičius

In this paper we give a precise estimate of the discrepancy of a class of uniformly distributed sequences of partitions. Among them we found a large class having low discrepancy (which means of order 1/N. One of them is the…

Classical Analysis and ODEs · Mathematics 2010-05-13 Ingrid Carbone

In this paper, for the generalized Fibonacci sequence $\left\{W_n\left(a,b,p,q\right)\right\}$, by using elementary methods and techniques, we give the asymptotic estimation values of…

Number Theory · Mathematics 2025-09-19 Yongkang Wan , Zhonghao Liang , Qunying Liao

For estimating a lower bounded parametric function in the framework of Marchand and Strawderman (2006), we provide through a unified approach a class of Bayesian confidence intervals with credibility $1-\alpha$ and frequentist coverage…

Statistics Theory · Mathematics 2012-12-21 Eric Marchand , William E. Strawderman

Divisibility sequences are defined by the property that their elements divide each other whenever their indices do. The divisibility sequences that also satisfy a linear recurrence, like the Fibonacci numbers, are generated by polynomials…

Number Theory · Mathematics 2022-06-22 Sergiy Koshkin

This Paper investigate sequent calculi for certain weak subintuitionistic logics. We establish that weakening and contraction are height-preserving admissible for each of these calculi, and we provide a syntactic proof for the admissibility…

Logic · Mathematics 2024-10-29 Fatemeh Shirmohammadzadeh Maleki

In this paper, we discuss about some results on average of Fibonacci and Lucas sequences that may be found in the OEIS code A111035.

Combinatorics · Mathematics 2020-02-03 Daniel Yaqubi , Amirali Fatehizadeh

In this paper we study the sets of integers which are $n$-th terms of Lucas sequences. We establish lower- and upper bounds for the size of these sets. These bounds are sharp for $n$ sufficiently large. We also develop bounds on the growth…

Number Theory · Mathematics 2024-08-12 L. Hajdu , R. Tijdeman

Given two sequences $A[1..n]$ and $B[1..m]$ over a totally ordered alphabet, the \emph{Longest Common Bitonic Subsequence} (LCBS) problem asks for a longest common subsequence that is strictly increasing up to a single peak element and…

Data Structures and Algorithms · Computer Science 2026-01-15 Md. Tanzeem Rahat , Md. Manzurul Hasan

In applications it is common that the exact form of a conditional expectation is unknown and having flexible functional forms can lead to improvements. Series method offers that by approximating the unknown function based on $k$ basis…

Methodology · Statistics 2017-10-05 Alexandre Belloni , Victor Chernozhukov , Denis Chetverikov , Kengo Kato

Non-linear least squares solvers are used across a broad range of offline and real-time model fitting problems. Most improvements of the basic Gauss-Newton algorithm tackle convergence guarantees or leverage the sparsity of the underlying…

Computer Vision and Pattern Recognition · Computer Science 2020-10-22 Huu Le , Christopher Zach , Edward Rosten , Oliver J. Woodford

Given an increasing sequence of integers a(n), it is known (due to Weyl) that for almost all reals t, the fractional parts of the dilated sequence t*a(n) are uniformly distributed in the unit interval. Some effort has been made recently to…

Number Theory · Mathematics 2007-05-23 Zeev Rudnick , Alexandru Zaharescu

Linear differential equations and recurrences reveal many properties about their solutions. Therefore, these equations are well-suited for representing solutions and computing with special functions. We identify a large class of existing…

Symbolic Computation · Computer Science 2026-01-14 Louis Gaillard

This paper studies the problems of identifiability and estimation in high-dimensional nonparametric latent structure models. We introduce an identifiability theorem that generalizes existing conditions, establishing a unified framework…

Statistics Theory · Mathematics 2025-08-06 Yichen Lyu , Pengkun Yang

The linear complexity and the $k$-error linear complexity of a binary sequence are important security measures for key stream strength. By studying binary sequences with the minimum Hamming weight, a new tool named as hypercube theory is…

Cryptography and Security · Computer Science 2014-08-13 Jianqin Zhou , Wanquan Liu , Guanglu Zhou

We present a certain generalization of a recent result of M. I. Cirnu on linear recurrence relations with coefficient in progressions [2]. We provide some interesting examples related to some well-known integer sequences, such as Fibonacci…

Number Theory · Mathematics 2015-03-19 Jerico B. Bacani , Julius Fergy T. Rabago

We revisit the classical problem of estimating an unknown distribution from its samples by fitting a mixture model that minimizes cross-entropy loss. Framing the task as a stochastic convex optimization problem over the space of $ M…

Machine Learning · Statistics 2026-05-26 Mohammadreza Ahmadypour , Tara Javidi , Farinaz Koushanfar
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