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Related papers: Maximum-order complexity and $2$-adic complexity

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The higher-order correlation clustering problem is an expressive model, and recently, local search heuristics have been proposed for several applications. Certifying optimality, however, is NP-hard and practically hampered already by the…

Discrete Mathematics · Computer Science 2023-04-03 David Stein , Silvia Di Gregorio , Bjoern Andres

Second-order polynomials generalize classical first-order ones in allowing for additional variables that range over functions rather than values. We are motivated by their applications in higher-order computational complexity theory,…

Logic in Computer Science · Computer Science 2023-05-23 Donghyun Lim , Martin Ziegler

Sublinear time algorithms for approximating maximum matching size have long been studied. Much of the progress over the last two decades on this problem has been on the algorithmic side. For instance, an algorithm of Behnezhad [FOCS'21]…

Data Structures and Algorithms · Computer Science 2022-11-30 Soheil Behnezhad , Mohammad Roghani , Aviad Rubinstein

In this paper, we present a computational search for best-known merit factors of longer binary sequences with an odd length. Finding low autocorrelation binary sequences with optimal or suboptimal merit factors is a very difficult…

Information Theory · Computer Science 2023-01-13 Janez Brest , Borko Bošković

We propose a study of structured non-convex non-concave min-max problems which goes beyond standard first-order approaches. Inspired by the tight understanding established in recent works [Adil et al., 2022, Lin and Jordan, 2022b], we…

Optimization and Control · Mathematics 2023-04-18 Abhijeet Vyas , Brian Bullins

In this paper, we introduce the n-th discrete topological complexity and study its properties such as its relation with simplicial Lusternik-Schnirelmann category and how the higher dimensions of discrete topological complexity relate with…

Algebraic Topology · Mathematics 2024-04-17 Hilal Alabay , Ayse Borat , Esra Cihangirli , Esma Dirican Erdal

Let $p$ be an odd prime with $2$-adic expansion $\sum_{i=0}^kp_i\cdot2^i$. For a sequence $\underline{a}=(a(t))_{t\ge 0}$ over $\mathbb{F}_{p}$, each $a(t)$ belongs to $\{0,1,\ldots, p-1\}$ and has a unique $2$-adic expansion…

Information Theory · Computer Science 2014-02-20 Yupeng Jiang , DongDai Lin

An orientable sequence of order $n$ is a cyclic binary sequence such that each length-$n$ substring appears at most once \emph{in either direction}. Maximal length orientable sequences are known only for $n\leq 7$, and a trivial upper bound…

Data Structures and Algorithms · Computer Science 2024-05-27 Daniel Gabric , Joe Sawada

Successive quadratic approximations, or second-order proximal methods, are useful for minimizing functions that are a sum of a smooth part and a convex, possibly nonsmooth part that promotes regularization. Most analyses of iteration…

Optimization and Control · Mathematics 2019-01-25 Ching-pei Lee , Stephen J. Wright

Over the past few decades, non-monotonic reasoning has developed to be one of the most important topics in computational logic and artificial intelligence. Different ways to introduce non-monotonic aspects to classical logic have been…

Computational Complexity · Computer Science 2010-09-13 Michael Thomas , Heribert Vollmer

Recursive decoding techniques are considered for Reed-Muller (RM) codes of growing length $n$ and fixed order $r.$ An algorithm is designed that has complexity of order $n\log n$ and corrects most error patterns of weight up to…

Information Theory · Computer Science 2017-03-17 Ilya Dumer

We consider the problem of minimal correction of the training set to make it consistent with monotonic constraints. This problem arises during analysis of data sets via techniques that require monotone data. We show that this problem is…

Machine Learning · Computer Science 2007-05-23 Rustem Takhanov

Finite-sum optimization problems are ubiquitous in machine learning, and are commonly solved using first-order methods which rely on gradient computations. Recently, there has been growing interest in \emph{second-order} methods, which rely…

Optimization and Control · Mathematics 2017-03-09 Yossi Arjevani , Ohad Shamir

Second-order methods, which utilize gradients as well as Hessians to optimize a given function, are of major importance in mathematical optimization. In this work, we prove tight bounds on the oracle complexity of such methods for smooth…

Optimization and Control · Mathematics 2017-08-18 Yossi Arjevani , Ohad Shamir , Ron Shiff

In this paper, we study the periodicity structure of finite field linear recurring sequences whose period is not necessarily maximal and determine necessary and sufficient conditions for the characteristic polynomial~\(f\) to have exactly…

Combinatorics · Mathematics 2021-03-02 Ghurumuruhan Ganesan

The theory of asymptotic complexity provides an approach to characterizing the behavior of programs in terms of bounds on the number of computational steps executed or use of computational resources. We describe work using ACL2 to prove…

Computational Complexity · Computer Science 2022-05-25 William D. Young

Ordinal classification problems, where labels exhibit a natural order, are prevalent in high-stakes fields such as medicine and finance. Accurate uncertainty quantification, including the decomposition into aleatoric (inherent variability)…

Machine Learning · Computer Science 2025-07-02 Stefan Haas , Eyke Hüllermeier

In this paper we investigate the existence and uniqueness of bounded, periodic and almost periodic solutions for second order differential equations involving reflection of the argument.The relationship between frequency modules of forced…

Classical Analysis and ODEs · Mathematics 2013-02-05 Daxiong Piao , Na Xin

On solving a convex-concave bilinear saddle-point problem (SPP), there have been many works studying the complexity results of first-order methods. These results are all about upper complexity bounds, which can determine at most how many…

Optimization and Control · Mathematics 2018-08-10 Yuyuan Ouyang , Yangyang Xu

Dual first-order methods are essential techniques for large-scale constrained convex optimization. However, when recovering the primal solutions, we need $T(\epsilon^{-2})$ iterations to achieve an $\epsilon$-optimal primal solution when we…

Numerical Analysis · Mathematics 2019-08-16 Huan Li , Zhouchen Lin