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In this paper we introduce constructible analogs of the discrete complexity classes $\mathbf{VP}$ and $\mathbf{VNP}$ of sequences of functions. The functions in the new definitions are constructible functions on $\mathbb{R}^n$ or…

Algebraic Geometry · Mathematics 2017-10-09 Saugata Basu

We introduce the notion of finitary computable reducibility on equivalence relations on the natural numbers. This is a weakening of the usual notion of computable reducibility, and we show it to be distinct in several ways. In particular,…

Logic · Mathematics 2018-02-12 Russell Miller , Keng Meng Ng

Seq2seq models have been shown to struggle with compositional generalisation, i.e. generalising to new and potentially more complex structures than seen during training. Taking inspiration from grammar-based models that excel at…

Computation and Language · Computer Science 2023-02-16 Matthias Lindemann , Alexander Koller , Ivan Titov

We propose a more general definition of generic-case complexity, based on using a random process for generating inputs of an algorithm and using the time needed to generate an input as a way of measuring the size of that input.

Computational Complexity · Computer Science 2015-05-14 Ilya Kapovich

We generalise the notion of separable equivalence, originally presented by Linckelmann (2011), to an equivalence relation on additive categories. We use this generalisation to show that from an initial equivalence between two algebras we…

Representation Theory · Mathematics 2017-11-01 Simon F Peacock

We describe the basic theory of infinite time Turing machines and some recent developments, including the infinite time degree theory, infinite time complexity theory, and infinite time computable model theory. We focus particularly on the…

Logic · Mathematics 2019-08-16 Samuel Coskey , Joel David Hamkins

We show that if the structural rules are admissible over a set R of atomic rules, then they are admissible in the sequent calculus obtained by adding the rules in R to G3[mic]. Two applications to pure logic and to the sequent calculus with…

Logic · Mathematics 2018-10-29 Franco Parlamento , Flavio Previale

Humans can systematically generalize to novel compositions of existing concepts. Recent studies argue that neural networks appear inherently ineffective in such cognitive capacity, leading to a pessimistic view and a lack of attention to…

Computation and Language · Computer Science 2022-10-19 Ning Shi , Boxin Wang , Wei Wang , Xiangyu Liu , Zhouhan Lin

The complexity of equivalence relations has received much attention in the recent literature. The main tool for such endeavour is the following reducibility: given equivalence relations $R$ and $S$ on natural numbers, $R$ is computably…

Logic · Mathematics 2023-11-09 Nikolay Bazhenov , Keng Meng Ng , Luca San Mauro , Andrea Sorbi

Quantum algorithms are sequences of abstract operations, performed on non-existent computers. They are in obvious need of categorical semantics. We present some steps in this direction, following earlier contributions of Abramsky, Coecke…

Quantum Physics · Physics 2016-11-09 Dusko Pavlovic

We present a swift walk-through of our recent work that uses machine learning to fit interatomic potentials based on quantum mechanical data. We describe our Gaussian Approximation Potentials (GAP) framework, discussing a variety of…

Materials Science · Physics 2020-02-06 Albert P. Bartók , Gábor Csányi

Finding a point in the intersection of a collection of closed convex sets, that is the convex feasibility problem, represents the main modeling strategy for many computational problems. In this paper we analyze new stochastic reformulations…

Optimization and Control · Mathematics 2018-01-16 Ion Necoara , Peter Richtarik , Andrei Patrascu

Most ideas about what an algorithm is are very similar. Basic operations are used for transforming objects. The evaluation of internal and external states by relations has impact on the further process. A more precise definition can lead to…

Logic · Mathematics 2025-02-26 Christine Gaßner

Graded Hecke algebras can be constructed geometrically, with constructible sheaves and equivariant cohomology. The input consists of a complex reductive group G (possibly disconnected) and a cuspidal local system on a nilpotent orbit for a…

Algebraic Geometry · Mathematics 2025-01-20 Maarten Solleveld

This paper studies generalized semi-infinite programs (GSIPs) defined with polyhedral parameter sets. Assume these GSIPs are given by polynomials. We propose a new approach to solve them as a disjunctive program. This approach is based on…

Optimization and Control · Mathematics 2025-07-25 Xiaomeng Hu , Jiawang Nie , Suhan Zhong

Complex structures are typical in machine learning. Tailoring learning algorithms for every structure requires an effort that may be saved by defining a generic learning procedure adaptive to any complex structure. In this paper, we propose…

Machine Learning · Computer Science 2019-05-28 Pablo Strasser , Stephane Armand , Stephane Marchand-Maillet , Alexandros Kalousis

Reproducible builds are a set of software development practices that establish an independently verifiable path from source code to binary artifacts, helping to detect and mitigate certain classes of supply chain attacks. Although quantum…

Quantum Physics · Physics 2025-10-03 Iyán Méndez Veiga , Esther Hänggi

We give an analysis and generalizations of some long-established constructive completeness results in terms of categorical logic and pre-sheaf and sheaf semantics. The purpose is in no small part conceptual and organizational: from a few…

Logic · Mathematics 2017-09-19 Henrik Forssell , Christian Espíndola

In this paper we focus on concurrent processes built on synchronization by means of futures. This concept is an abstraction for processes based on a main execution thread but allowing to delay some computations. The structure of a general…

Discrete Mathematics · Computer Science 2018-03-05 Olivier Bodini , Matthieu Dien , Antoine Genitrini , Alfredo Viola

We study sequential prediction of real-valued, arbitrary and unknown sequences under the squared error loss as well as the best parametric predictor out of a large, continuous class of predictors. Inspired by recent results from…

Machine Learning · Computer Science 2014-01-24 N. Denizcan Vanli , Suleyman S. Kozat