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An uncomplicated and easily handling prescription that converts the task of checking the unitarity of massive, topologically massive, models into a straightforward algebraic exercise, is developed. The algorithm is used to test the…

High Energy Physics - Theory · Physics 2009-11-11 Antonio Accioly , Marco Dias

We consider the following decision problem: given two simply typed $\lambda$-terms, are they $\beta$-convertible? Equivalently, do they have the same normal form? It is famously non-elementary, but the precise complexity - namely…

Logic in Computer Science · Computer Science 2024-09-11 Lê Thành Dũng Nguyên

In this article we will build a universal imbedding of a regular Hom- Lie triple system into a Lie algebra and show that the category of regular Hom-Lie triple systems is equivalent to a full subcategory of pairs of…

Rings and Algebras · Mathematics 2017-09-27 Robert Vandermolen

Overparameterized neural networks can be highly accurate on average on an i.i.d. test set yet consistently fail on atypical groups of the data (e.g., by learning spurious correlations that hold on average but not in such groups).…

Machine Learning · Computer Science 2020-04-03 Shiori Sagawa , Pang Wei Koh , Tatsunori B. Hashimoto , Percy Liang

We present an algorithm to decide the intruder deduction problem (IDP) for a class of locally stable theories enriched with normal forms. Our result relies on a new and efficient algorithm to solve a restricted case of higher-order…

Logic in Computer Science · Computer Science 2013-04-01 Mauricio Ayala-Rincón , Maribel Fernández , Daniele Nantes-Sobrinho

All versions of this paper contain errors. Therefore, the existence of an oracle relative to which (i) there exist complete disjoint coNP-pairs and (ii) there exist no complete total polynomial search problems must be considered as an open…

Computational Complexity · Computer Science 2019-11-21 Titus Dose

We consider the problem of hypothesis testing for discrete distributions. In the standard model, where we have sample access to an underlying distribution $p$, extensive research has established optimal bounds for uniformity testing,…

Machine Learning · Computer Science 2024-12-03 Maryam Aliakbarpour , Piotr Indyk , Ronitt Rubinfeld , Sandeep Silwal

We show that the (typical) quantitative considerations about proper (as too big) and small classes are just tangential facts regarding the consistency of Zermelo-Fraenkel Set Theory with Choice. Effectively, we will construct a first-order…

Logic · Mathematics 2018-04-10 Danny A. J. Gomez-Ramirez

In this paper we describe how to leverage higher-order unification to type check a dependently typed language with meta-variables. The literature usually presents the unification algorithm as a standalone component, however the need to…

Programming Languages · Computer Science 2016-10-03 Francesco Mazzoli , Andreas Abel

The Dependent Object Types (DOT) calculus formalizes key features of Scala. The D$_{<: }$ calculus is the core of DOT. To date, presentations of D$_{<: }$ have used declarative typing and subtyping rules, as opposed to algorithmic.…

Programming Languages · Computer Science 2017-09-29 Abel Nieto

Instances of logical cryptanalysis, circuit verification, and bounded model checking can often be succinctly represented as a combined satisfiability (SAT) problem where an instance is a combination of traditional clauses and parity…

Logic in Computer Science · Computer Science 2012-09-11 Tero Laitinen , Tommi Junttila , Ilkka Niemelä

Among the finitely generated modules over a Noetherian ring R, the semidualizing modules have been singled out due to their particularly nice duality properties. When R is a normal domain, we exhibit a natural inclusion of the set of…

Commutative Algebra · Mathematics 2007-05-23 Sean Sather-Wagstaff

Concolic testing is a popular dynamic validation technique that can be used for both model checking and automatic test case generation. We have recently introduced concolic testing in the context of logic programming. In contrast to…

Logic in Computer Science · Computer Science 2016-08-11 Fred Mesnard , Etienne Payet , German Vidal

The prediction accuracy of machine learning methods is steadily increasing, but the calibration of their uncertainty predictions poses a significant challenge. Numerous works focus on obtaining well-calibrated predictive models, but less is…

Machine Learning · Statistics 2023-12-07 Donghwan Lee , Xinmeng Huang , Hamed Hassani , Edgar Dobriban

In order to properly train a machine learning model, data must be properly collected. To guarantee a proper data collection, verifying that the collected data set holds certain properties is a possible solution. For example, guaranteeing…

Software Engineering · Computer Science 2021-08-26 Jorge López , Maxime Labonne , Claude Poletti

The logical technique of focusing can be applied to the $\lambda$-calculus; in a simple type system with atomic types and negative type formers (functions, products, the unit type), its normal forms coincide with $\beta\eta$-normal forms.…

Programming Languages · Computer Science 2016-11-09 Gabriel Scherer

In this paper we look at a class of random optimization problems. We discuss ways that can help determine typical behavior of their solutions. When the dimensions of the optimization problems are large such an information often can be…

Information Theory · Computer Science 2013-04-01 Mihailo Stojnic

We consider the simulation of distributions that are a mixture of discrete and continuous components. We extend a Metropolis-Hastings-based perfect sampling algorithm of Corcoran and Tweedie to allow for a broader class of transition…

Methodology · Statistics 2012-02-02 Wenjin Mao , Jem Corcoran

It is well known that the resolution method (for propositional logic) is complete. However, completeness proofs found in the literature use an argument by contradiction showing that if a set of clauses is unsatisfiable, then it must have a…

Logic in Computer Science · Computer Science 2017-01-11 Jean Gallier

In this paper, we treat the problem of testing for normality as a binary classification problem and construct a feedforward neural network that can successfully detect normal distributions by inspecting small samples from them. The…

Machine Learning · Statistics 2020-10-08 Miloš Simić