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Modern cryptography is largely based on complexity assumptions, for example, the ubiquitous RSA is based on the supposed complexity of the prime factorization problem. Thus, it is of fundamental importance to understand how a quantum…

Quantum Physics · Physics 2016-01-20 Jose Luis Rosales

Fermion sampling is to generate probability distribution of a many-body Slater-determinant wavefunction, which is termed "determinantal point process" in statistical analysis. For its inherently-embedded Pauli exclusion principle, its…

Quantum Physics · Physics 2023-01-31 Haoran Sun , Jie Zou , Xiaopeng Li

The works presented in this habilitation concern the algorithmics of polynomials. This is a central topic in computer algebra, with numerous applications both within and outside the field - cryptography, error-correcting codes, etc. For…

Symbolic Computation · Computer Science 2026-03-09 Bruno Grenet

We propose a Fourier-based learning algorithm for highly nonlinear multiclass classification. The algorithm is based on a smoothing technique to calculate the probability distribution of all classes. To obtain the probability distribution,…

Machine Learning · Computer Science 2022-11-17 Soheil Mehrabkhani

An inverse nonequispaced fast Fourier transform (iNFFT) is a fast algorithm to compute the Fourier coefficients of a trigonometric polynomial from nonequispaced sampling data. However, various applications such as magnetic resonance imaging…

Numerical Analysis · Mathematics 2025-06-09 Melanie Kircheis , Daniel Potts

Sample- and computationally-efficient distribution estimation is a fundamental tenet in statistics and machine learning. We present SURF, an algorithm for approximating distributions by piecewise polynomials. SURF is: simple, replacing…

Machine Learning · Statistics 2021-02-15 Yi Hao , Ayush Jain , Alon Orlitsky , Vaishakh Ravindrakumar

Given a Boolean function f, the (Hamming) weight wt(f) and the nonlinearity N(f) are well known to be important in designing functions that are useful in cryptography. The nonlinearity is expensive to compute, in general, so any shortcuts…

Information Theory · Computer Science 2018-02-19 Thomas W. Cusick

Given a square, nonsingular matrix of univariate polynomials $\mathbf{F}\in\mathbb{K}[x]^{n\times n}$ over a field $\mathbb{K}$, we give a deterministic algorithm for finding the determinant of $\mathbf{F}$. The complexity of the algorithm…

Symbolic Computation · Computer Science 2014-09-22 Wei Zhou , George Labahn

In this paper we study the complexity of factorization of polynomials in the free noncommutative ring $\mathbb{F}\langle x_1,x_2,\dots,x_n\rangle$ of polynomials over the field $\mathbb{F}$ and noncommuting variables $x_1,x_2,\ldots,x_n$.…

Computational Complexity · Computer Science 2015-01-06 V. Arvind , Pushkar S Joglekar , Gaurav Rattan

The existence of string functions, which are not polynomial time computable, but whose graph is checkable in polynomial time, is a basic assumption in cryptography. We prove that in the framework of algebraic complexity, there are no such…

Computational Complexity · Computer Science 2018-12-18 Peter Bürgisser

Let $f : \mathbf{N} \rightarrow \mathbf{C}$ be a bounded multiplicative function. Let $a$ be a fixed integer (say $a = 1$). Then $f$ is well-distributed on the progression $n \equiv a \pmod{q} \subset \{1,\dots, X\}$, for almost all primes…

Number Theory · Mathematics 2018-04-24 Ben Green

Feature selection is a widely used dimension reduction technique to select feature subsets because of its interpretability. Many methods have been proposed and achieved good results, in which the relationships between adjacent data points…

Machine Learning · Computer Science 2020-06-01 Yan Min , Mao Ye , Liang Tian , Yulin Jian , Ce Zhu , Shangming Yang

There has been a recent critical need to study fairness and bias in machine learning (ML) algorithms. Since there is clearly no one-size-fits-all solution to fairness, ML methods should be developed alongside bias mitigation strategies that…

Machine Learning · Computer Science 2026-03-06 Lara Kassab , Erin George , Deanna Needell , Haowen Geng , Nika Jafar Nia , Aoxi Li

We consider the problem of estimating an arbitrary smooth functional of $k \geq 1 $ distribution functions (d.f.s.) in terms of random samples from them. The natural estimate replaces the d.f.s by their empirical d.f.s. Its bias is…

Statistics Theory · Mathematics 2010-08-03 C. S. Withers , S. Nadarajah

Let $\phi(n)$ be the Euler-phi function, define $\phi_0(n) = n$ and $\phi_{k+1}(n)=\phi(\phi_{k}(n))$ for all $k\geq 0$. We will determine an asymptotic formula for the set of integers $n$ less than $x$ for which $\phi_k(n)$ is $y$-smooth,…

Number Theory · Mathematics 2010-05-26 Youness Lamzouri

For any $d \geq 1$, random $\mathbb{Z}^d$ shifts of finite type (SFTs) were defined in previous work of the authors. For a parameter $\alpha \in [0,1]$, an alphabet $\mathcal{A}$, and a scale $n \in \mathbb{N}$, one obtains a distribution…

Dynamical Systems · Mathematics 2017-05-02 Kevin McGoff , Ronnie Pavlov

Newton iteration (NI) is an almost 350 years old recursive formula that approximates a simple root of a polynomial quite rapidly. We generalize it to a matrix recurrence (allRootsNI) that approximates all the roots simultaneously. In this…

Computational Complexity · Computer Science 2017-10-10 Pranjal Dutta , Nitin Saxena , Amit Sinhababu

It is known that the Frank-Wolfe (FW) algorithm, which is affine-covariant, enjoys accelerated convergence rates when the constraint set is strongly convex. However, these results rely on norm-dependent assumptions, usually incurring…

Optimization and Control · Mathematics 2020-11-09 Thomas Kerdreux , Lewis Liu , Simon Lacoste-Julien , Damien Scieur

We study the canonical Hodge filtration on the sheaf $\mathscr{O}_X(*D)$ of meromorphic functions along a divisor. For a germ of an analytic function $f$ whose Bernstein-Sato's polynomial's roots are contained in $(-2,0)$, we: give a simple…

Algebraic Geometry · Mathematics 2024-08-06 Daniel Bath , Henry Dakin

Let $\mathcal{F}_{n}^*$ be the set of Boolean functions depending on all $n$ variables. We prove that for any $f\in \mathcal{F}_{n}^*$, $f|_{x_i=0}$ or $f|_{x_i=1}$ depends on the remaining $n-1$ variables, for some variable $x_i$. This…

Computational Complexity · Computer Science 2015-02-05 Chia-Jung Lee , Satya V. Lokam , Shi-Chun Tsai , Ming-Chuan Yang