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In this paper we give an ordinal analysis of the theory of second order arithmetic. We do this by working with proof trees -- that is, "deductions" which may not be well-founded. Working in a suitable theory, we are able to represent…

Logic · Mathematics 2024-03-27 Henry Towsner

In this paper, we investigate the power of nearly purely operational techniques in the study of umbral calculus. We present a concise reconstruction of the theory based on a systematic use of linear operators, with particular attention to…

Combinatorics · Mathematics 2025-12-05 Kei Beauduin

The question of obtaining well-defined criteria for multiple criteria decision making problems is well-known. One of the approaches dealing with this question is the concept of nonessential objective function. A certain objective function…

Optimization and Control · Mathematics 2008-11-08 Agnieszka B. Malinowska , Delfim F. M. Torres

Much work has been done on extending the well-founded semantics to general disjunctive logic programs and various approaches have been proposed. However, these semantics are different from each other and no consensus is reached about which…

Artificial Intelligence · Computer Science 2007-05-23 Kewen Wang , Lizhu Zhou

Replacing operators with continuous operator-valued functions, we prove time-dependent versions of well-known results on compressions and diagonals of bounded operators. The setting of smooth functions is also addressed. Our results have no…

Functional Analysis · Mathematics 2025-12-18 Vladimir Müller , Yuri Tomilov

The octagon abstract domain is a widely used numeric abstract domain expressing relational information between variables whilst being both computationally efficient and simple to implement. Each element of the domain is a system of…

Programming Languages · Computer Science 2017-11-01 Aziem Chawdhary , Ed Robbins , Andy King

Functional Distributional Semantics is a framework that aims to learn, from text, semantic representations which can be interpreted in terms of truth. Here we make two contributions to this framework. The first is to show how a type of…

Computation and Language · Computer Science 2017-09-04 Guy Emerson , Ann Copestake

In this paper we explore orthogonal systems in $\mathrm{L}_2(\mathbb{R})$ which give rise to a skew-Hermitian, tridiagonal differentiation matrix. Surprisingly, allowing the differentiation matrix to be complex leads to a particular family…

Numerical Analysis · Mathematics 2019-11-21 Arieh Iserles , Marcus Webb

The main objective of explanations is to transmit knowledge to humans. This work proposes to construct informative explanations for predictions made from machine learning models. Motivated by the observations from social sciences, our…

Artificial Intelligence · Computer Science 2018-05-29 Freddy Lecue , Jiewen Wu

Iterative refinement -- start with a random guess, then iteratively improve the guess -- is a useful paradigm for representation learning because it offers a way to break symmetries among equally plausible explanations for the data. This…

Machine Learning · Computer Science 2023-01-03 Michael Chang , Thomas L. Griffiths , Sergey Levine

Reasoning with defeasible and conflicting knowledge in an argumentative form is a key research field in computational argumentation. Reasoning under various forms of uncertainty is both a key feature and a challenging barrier for automated…

Artificial Intelligence · Computer Science 2024-07-09 Andrei Popescu , Johannes P. Wallner

Logic-based approaches to AI have the advantage that their behavior can in principle be explained with the help of proofs of the computed consequences. For ontologies based on Description Logic (DL), we have put this advantage into practice…

Logic in Computer Science · Computer Science 2023-08-08 Christian Alrabbaa , Franz Baader , Stefan Borgwardt , Patrick Koopmann , Alisa Kovtunova

Machine learning systems perform well on pattern matching tasks, but their ability to perform algorithmic or logical reasoning is not well understood. One important reasoning capability is algorithmic extrapolation, in which models trained…

Machine Learning · Computer Science 2022-10-18 Arpit Bansal , Avi Schwarzschild , Eitan Borgnia , Zeyad Emam , Furong Huang , Micah Goldblum , Tom Goldstein

Many popular policy gradient methods for reinforcement learning follow a biased approximation of the policy gradient known as the discounted approximation. While it has been shown that the discounted approximation of the policy gradient is…

Machine Learning · Computer Science 2023-01-10 Chris Nota

The paper considers asymptotics of summation functions of additive and multiplicative arithmetic functions. We also study asymptotics of summation functions of natural and prime arguments. Several assertions on this subject are proved and…

General Mathematics · Mathematics 2022-10-07 Victor Volfson

The ability to conduct logical reasoning is a fundamental aspect of intelligent human behavior, and thus an important problem along the way to human-level artificial intelligence. Traditionally, logic-based symbolic methods from the field…

Artificial Intelligence · Computer Science 2021-01-11 Patrick Hohenecker , Thomas Lukasiewicz

We uncover a close relationship between combinatorial and syntactic proofs for first-order logic (without equality). Whereas syntactic proofs are formalized in a deductive proof system based on inference rules, a combinatorial proof is a…

Logic in Computer Science · Computer Science 2021-04-28 Dominic Hughes , Lutz Straßburger , Jui-Hsuan Wu

Unlike polynomials, rational functions can represent functions having poles or branch cuts with root-exponential convergence and no Runge phenomenon. Recent developments of the AAA and greedy Thiele algorithms have sparked renewed interest…

Numerical Analysis · Mathematics 2025-12-09 Tobin A. Driscoll

We analyze Coquand's game-theoretic interpretation of Peano Arithmetic through the lens of elementary descent recursion. In Coquand's game semantics, winning strategies correspond to infinitary cut-free proofs and cut elimination…

Logic · Mathematics 2024-12-02 Emanuele Frittaion

In Constraint Programming, constraints are usually represented as predicates allowing or forbidding combinations of values. However, some algorithms exploit a finer representation: error functions. Their usage comes with a price though: it…

Artificial Intelligence · Computer Science 2023-03-09 Florian Richoux , Jean-François Baffier