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As a prominent attribution-based explanation algorithm, Integrated Gradients (IG) is widely adopted due to its desirable explanation axioms and the ease of gradient computation. It measures feature importance by averaging the model's output…

Computation and Language · Computer Science 2021-09-01 Soumya Sanyal , Xiang Ren

This work deals with the problem of choosing a time step for the numerical solution of boundary value problems for parabolic equations. The problem solution is derived using the fully implicit scheme, whereas a time step is selected via…

Numerical Analysis · Computer Science 2013-11-13 Petr N. Vabishchevich

Interval analysis (or interval bound propagation, IBP) is a popular technique for verifying and training provably robust deep neural networks, a fundamental challenge in the area of reliable machine learning. However, despite substantial…

Machine Learning · Computer Science 2021-12-15 Matthew Mirman , Maximilian Baader , Martin Vechev

While concepts and tools from Theoretical Computer Science are regularly applied to, and significantly support, software development for discrete problems, Numerical Engineering largely employs recipes and methods whose correctness and…

Computational Complexity · Computer Science 2018-01-23 Akitoshi Kawamura , Martin Ziegler

The forgotten topological index or F-index of a graph is defined as the sum of degree cube of all the vertices of the graph. This index was introduced by Gutman and Trinajesti\'{c} more than 40 years ago. In this paper, we derive F-index of…

Combinatorics · Mathematics 2017-09-20 Prosanta Sarkar , Nilanjan De , Anita Pal

Differentiable optimization layers enable learning systems to make decisions by solving embedded optimization problems. However, computing gradients via implicit differentiation requires solving a linear system with Hessian terms, which is…

Machine Learning · Computer Science 2025-12-03 Zihao Zhao , Kai-Chia Mo , Shing-Hei Ho , Brandon Amos , Kai Wang

In this paper, we investigate the trade-off between convergence rate and computational cost when minimizing a composite functional with proximal-gradient methods, which are popular optimisation tools in machine learning. We consider the…

Machine Learning · Computer Science 2012-10-23 Pierre Machart , Sandrine Anthoine , Luca Baldassarre

We describe an approximate rational arithmetic with round-off errors (both absolute and relative) controlled by the user. The rounding procedure is based on the continued fraction expansion of real numbers. Results of computer experiments…

Numerical Analysis · Mathematics 2025-10-20 Grigori Litvinov , Anatoli Rodionov , Andrei Chourkin

Based on the recent breakthrough of Huang (2019), we show that for any total Boolean function $f$, $\bullet \quad \mathrm{deg}(f) = O(\widetilde{\mathrm{deg}}(f)^2)$: The degree of $f$ is at most quadratic in the approximate degree of $f$.…

Quantum Physics · Physics 2020-10-27 Scott Aaronson , Shalev Ben-David , Robin Kothari , Shravas Rao , Avishay Tal

The structure of the F5 algorithm to compute Gr\"obner bases makes it very efficient. However, while it is believed to terminate for so-called regular sequences, it is not clear whether it terminates for all inputs. This paper has two major…

Commutative Algebra · Mathematics 2012-02-29 Christian Eder , Justin Gash , John Perry

A T-curve of degree $d$ is given by a regular unimodular triangulation of $d \cdot \Delta_2$ together with a sign distribution on its lattice points. By Viro's Patchworking Theorem, this determines the ambient isotopy type (a.k.a. real…

Topology is the foundation for many industrial applications ranging from CAD to simulation analysis. Computational topology mostly focuses on structured data such as mesh, however unstructured dataset such as point set remains a virgin land…

Computational Geometry · Computer Science 2023-03-14 Hao Wang

Uncertainty quantification for estimation through stochastic optimization solutions in an online setting has gained popularity recently. This paper introduces a novel inference method focused on constructing confidence intervals with…

Machine Learning · Statistics 2026-03-24 Wanrong Zhu , Zhipeng Lou , Ziyang Wei , Wei Biao Wu

Multi-degree splines are piecewise polynomial functions having sections of different degrees. They offer significant advantages over the classical uniform-degree framework, as they allow for modeling complex geometries with fewer degrees of…

Numerical Analysis · Mathematics 2021-02-08 Carolina Vittoria Beccari , Giulio Casciola

The \emph{distance-number} of a graph $G$ is the minimum number of distinct edge-lengths over all straight-line drawings of $G$ in the plane. This definition generalises many well-known concepts in combinatorial geometry. We consider the…

Combinatorics · Mathematics 2008-09-09 Paz Carmi , Vida Dujmović , Pat Morin , David R. Wood

We prove that the degrees of the iterates ${\rm deg}(f^n)$ of a birational map satisfy $\liminf({\rm deg}(f^n))<+\infty$ if and only if the sequence ${\rm deg}(f^n)$ is bounded, and that the growth of ${\rm deg}(f^n)$ can not be arbitrarily…

Algebraic Geometry · Mathematics 2019-01-09 Serge Cantat , Junyi Xie

We study the set of chords of a real-valued continuous function on [0,1] with f(0)=f(1)=0. We describe which chords may appear as isolated points and provide examples illustrating our characterization. Maximal Hopf sets are introduced and…

General Topology · Mathematics 2026-01-27 Ion Ciudin , Eugen J. Ionascu

Data generated in the fields of science, technology, business and in many other fields of research are increasing in an exponential rate. The way to extract knowledge from a huge set of data is a challenging task. This paper aims to propose…

Information Retrieval · Computer Science 2010-03-23 P. G. JansiRani , R. Bhaskaran

We present new methods of automating the construction of index pairs, essential ingredients of discrete Conley index theory. These new algorithms are further steps in the direction of automating computer-assisted proofs of semi-conjugacies…

Dynamical Systems · Mathematics 2023-05-26 Rafael M. Frongillo , Rodrigo Treviño

We study a particular class of autonomous Differential-Algebraic Equations that are equivalent to Ordinary Differential Equations on manifolds. Under appropriate assumptions we determine an easy-to-use straightforward formula for the…

Classical Analysis and ODEs · Mathematics 2009-08-14 Marco Spadini