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In the context of functional data analysis, probability density functions as non-negative functions are characterized by specific properties of scale invariance and relative scale which enable to represent them with the unit integral…

Numerical Analysis · Mathematics 2019-12-19 Jitka Machalova , Renata Talska , Karel Hron , Ales Gaba

Let $p$ be a prime. Given a polynomial in $\F_{p^m}[x]$ of degree $d$ over the finite field $\F_{p^m}$, one can view it as a map from $\F_{p^m}$ to $\F_{p^m}$, and examine the image of this map, also known as the value set. In this paper,…

Number Theory · Mathematics 2011-11-07 Qi Cheng , Joshua E. Hill , Daqing Wan

SHAP explanations are a popular feature-attribution mechanism for explainable AI. They use game-theoretic notions to measure the influence of individual features on the prediction of a machine learning model. Despite a lot of recent…

Artificial Intelligence · Computer Science 2021-02-02 Guy Van den Broeck , Anton Lykov , Maximilian Schleich , Dan Suciu

In this paper, we consider the counting function $E_P(y) = |P_{y} \cap Z^{n_x}|$ for a parametric polyhedron $P_{y} = \{x \in R^{n_x} \colon A x \leq b + B y\}$, where $y \in R^{n_y}$. We give a new representation of $E_P(y)$, called a…

Data Structures and Algorithms · Computer Science 2024-12-05 D. Gribanov , D. Malyshev , P. Pardalos , N. Zolotykh

The number partition problem is a well-known problem, which is one of 21 Karp's NP-complete problems \cite{karp}. The partition function is a boolean function that is equivalent to the number partition problem with number range restricted.…

Computational Complexity · Computer Science 2022-12-25 Chuyu Xiong

A hypothesis testing algorithm is replicable if, when run on two different samples from the same distribution, it produces the same output with high probability. This notion, defined by by Impagliazzo, Lei, Pitassi, and Sorell [STOC'22],…

Data Structures and Algorithms · Computer Science 2025-09-05 Anders Aamand , Maryam Aliakbarpour , Justin Y. Chen , Shyam Narayanan , Sandeep Silwal

It is consistent that there is a partial order (P,<) of size aleph_1 such that every monotone (unary) function from P to P is first order definable in (P,<). The partial order is constructed in an extension obtained by finite support…

Logic · Mathematics 2016-09-07 Martin Goldstern , Saharon Shelah

This paper is concerned with the complexity analysis of constructor term rewrite systems and its ramification in implicit computational complexity. We introduce a path order with multiset status, the polynomial path order POP*, that is…

Logic in Computer Science · Computer Science 2015-07-01 Martin Avanzini , Georg Moser

We exhibit a sound and complete implicit-complexity formalism for functions feasibly computable by structural recursions over inductively defined data structures. Feasibly computable here means that the structural-recursive definition runs…

Computational Complexity · Computer Science 2022-05-23 Norman Danner , James S. Royer

Population protocols are a distributed computing model appropriate for describing massive numbers of agents with limited computational power. A population protocol "has an initial leader" if every valid initial configuration contains a…

Distributed, Parallel, and Cluster Computing · Computer Science 2018-11-06 Amanda Belleville , David Doty , David Soloveichik

We use weighted polynomial approximation to prove the existence of a compact set K with non-empty interior and a function f is dense in the space A(K) of all continuous functions on K that are holomorphic in the interior of K, endowed with…

Complex Variables · Mathematics 2025-06-26 Stéphane Charpentier , Konstantinos Maronikolakis

We consider the problem of ranking a set of OT constraints in a manner consistent with data. We speed up Tesar and Smolensky's RCD algorithm to be linear on the number of constraints. This finds a ranking so each attested form x_i beats or…

Computation and Language · Computer Science 2007-05-23 Jason Eisner

We investigate the problem of cryptanalysis as a problem belonging to the class NP. A class of problems UF is defined for which the time constructing any feasible solution is polynomial. The properties of the problems of NP, which may be…

Computational Complexity · Computer Science 2015-03-19 Anatoly D. Plotnikov

In Machine Learning, the $\mathsf{SHAP}$-score is a version of the Shapley value that is used to explain the result of a learned model on a specific entity by assigning a score to every feature. While in general computing Shapley values is…

Artificial Intelligence · Computer Science 2023-03-31 Marcelo Arenas , Pablo Barceló , Leopoldo Bertossi , Mikaël Monet

We construct efficient data structures that are resilient against a constant fraction of adversarial noise. Our model requires that the decoder answers most queries correctly with high probability and for the remaining queries, the decoder…

Data Structures and Algorithms · Computer Science 2010-01-27 Victor Chen , Elena Grigorescu , Ronald de Wolf

For a Boolean function $\Phi\colon\{0,1\}^d\to\{0,1\}$ and an assignment to its variables $\mathbf{x}=(x_1, x_2, \dots, x_d)$ we consider the problem of finding the subsets of the variables that are sufficient to determine the function…

Computational Complexity · Computer Science 2019-06-19 Stephan Wäldchen , Jan Macdonald , Sascha Hauch , Gitta Kutyniok

Given a p-order A over a universe of strings (i.e., a transitive, reflexive, antisymmetric relation such that if (x, y) is an element of A then |x| is polynomially bounded by |y|), an interval size function of A returns, for each string x…

Computational Complexity · Computer Science 2016-08-31 Lane A. Hemaspaandra , Christopher M. Homan , Sven Kosub , Klaus W. Wagner

We define an enumerative function F(n,k,P,m) which is a generalization of binomial coefficients. Special cases of this function are also power function, factorials, rising factorials and falling factorials. The first section of the paper is…

Combinatorics · Mathematics 2008-01-19 Milan Janjic

Many researchers in artificial intelligence are beginning to explore the use of soft constraints to express a set of (possibly conflicting) problem requirements. A soft constraint is a function defined on a collection of variables which…

Artificial Intelligence · Computer Science 2011-07-04 D. Cohen , M. Cooper , P. Jeavons , A. Krokhin

We introduce a new clustering method for the classification of functional data sets by their probabilistic law, that is, a procedure that aims to assign data sets to the same cluster if and only if the data were generated with the same…

Methodology · Statistics 2023-12-29 Antonio Galves , Fernando Najman , Marcela Svarc , Claudia D. Vargas