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Extended resolution shows that auxiliary variables are very powerful in theory. However, attempts to exploit this potential in practice have had limited success. One reasonably effective method in this regard is bounded variable addition…

Logic in Computer Science · Computer Science 2023-07-06 Andrew Haberlandt , Harrison Green , Marijn J. H. Heule

This paper presents a cut-elimination proof for the logic $LG^\omega$, which is an extension of a proof system for encoding generic judgments, the logic $\FOLDNb$ of Miller and Tiu, with an induction principle. The logic $LG^\omega$, just…

Logic in Computer Science · Computer Science 2008-01-22 Alwen Tiu

The cut-elimination procedure for the provability logic is known to be problematic: a L\"ob-like rule keeps cut-formulae intact on reduction, even in the principal case, thereby complicating the proof of termination. In this paper, we…

Logic in Computer Science · Computer Science 2025-01-03 Akinori Maniwa , Ryo Kashima

In this work we propose a multi-valued extension of logic programs under the stable models semantics where each true atom in a model is associated with a set of justifications, in a similar spirit than a set of proof trees. The main…

Artificial Intelligence · Computer Science 2013-12-24 Pedro Cabalar , Jorge Fandinno

Concept Activation Vectors (CAVs) provide a powerful approach for interpreting deep neural networks by quantifying their sensitivity to human-defined concepts. However, when computed independently at different layers, CAVs often exhibit…

Computer Vision and Pattern Recognition · Computer Science 2025-09-11 Zhenghao He , Sanchit Sinha , Guangzhi Xiong , Aidong Zhang

The support vector machine (SVM) is a widely used method for classification. Although many efforts have been devoted to develop efficient solvers, it remains challenging to apply SVM to large-scale problems. A nice property of SVM is that…

Machine Learning · Computer Science 2013-10-29 Jie Wang , Peter Wonka , Jieping Ye

The present paper provides an analysis of the existing proof systems for dynamic epistemic logic from the viewpoint of proof-theoretic semantics. Dynamic epistemic logic is one of the best known members of a family of logical systems which…

Intuitionistic grammar logics fuse constructive and multi-modal reasoning while permitting the use of converse modalities, serving as a generalization of standard intuitionistic modal logics. In this paper, we provide definitions of these…

Logic in Computer Science · Computer Science 2025-12-04 Tim S. Lyon

Studying unified model averaging estimation for situations with complicated data structures, we propose a novel model averaging method based on cross-validation (MACV). MACV unifies a large class of new and existing model averaging…

Methodology · Statistics 2024-12-16 Dalei Yu , Xinyu Zhang , Hua Liang

Variational regression methods are an increasingly popular tool for their efficient estimation of complex. Given the mixed model representation of penalized effects, additive regression models with smoothed effects and scalar-on-function…

Methodology · Statistics 2024-06-13 Mark J. Meyer , Junyi Wei

We investigate cut-elimination and cut-simulation in impredicative (higher-order) logics. We illustrate that adding simple axioms such as Leibniz equations to a calculus for an impredicative logic -- in our case a sequent calculus for…

Logic in Computer Science · Computer Science 2019-03-14 Christoph Benzmueller , Chad E. Brown , Michael Kohlhase

Assertion-Based Verification (ABV) is a crucial method for ensuring that logic designs conform to their architectural specifications. However, existing assertion generation methods primarily rely on information either from the design…

Hardware Architecture · Computer Science 2025-09-19 Yonghao Wang , Jiaxin Zhou , Hongqin Lyu , Zhiteng Chao , Tiancheng Wang , Huawei Li

The paper studies a cluster of systems for fully disquotational truth based on the restriction of initial sequents. Unlike well-known alternative approaches, such systems display both a simple and intuitive model theory and remarkable…

Logic · Mathematics 2020-06-30 Carlo Nicolai

Ill-founded (or non-wellfounded) proof systems have emerged as a natural framework for inductive and coinductive reasoning. In such systems, soundness relies on global correctness criteria, such as the progressivity condition. Ensuring that…

Logic in Computer Science · Computer Science 2026-02-16 Gianluca Curzi , Graham E. Leigh

Je\v{r}\'abek showed that cuts in classical propositional logic proofs in deep inference can be eliminated in quasipolynomial time. The proof is indirect and it relies on a result of Atserias, Galesi and Pudl\'ak about monotone sequent…

Computational Complexity · Computer Science 2017-01-11 Paola Bruscoli , Alessio Guglielmi , Tom Gundersen , Michel Parigot

Advances in deep learning and representation learning have transformed item factor analysis (IFA) in the item response theory (IRT) literature by enabling more efficient and accurate parameter estimation. Variational Autoencoders (VAEs)…

Machine Learning · Statistics 2025-11-03 Nanyu Luo , Feng Ji

We present a syntactic cut-elimination procedure for the alternation-free fragment of the modal mu-calculus. Cut reduction is carried out within a cyclic proof system, where proofs are finitely branching but may be non-wellfounded. The…

Logic in Computer Science · Computer Science 2025-10-14 Bahareh Afshari , Johannes Kloibhofer

We examine some combinatorial properties of parallel cut elimination in multiplicative linear logic (MLL) proof nets. We show that, provided we impose a constraint on some paths, we can bound the size of all the nets satisfying this…

Logic in Computer Science · Computer Science 2023-06-22 Jules Chouquet , Lionel Vaux Auclair

Today's programmers face a false choice between creating software that is extensible and software that is correct. Specifically, dynamic languages permit software that is richly extensible (via dynamic code loading, dynamic object…

Programming Languages · Computer Science 2016-08-23 Matthew A. Hammer , Bor-Yuh Evan Chang , David Van Horn

Whether deterministic or stochastic, models can be viewed as functions designed to approximate a specific quantity of interest. We introduce Minimal Empirical Variance Aggregation (MEVA), a data-driven framework that integrates predictions…

Machine Learning · Computer Science 2025-03-04 Théo Bourdais , Houman Owhadi