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Many semantical aspects of programming languages, such as their operational semantics and their type assignment calculi, are specified by describing appropriate proof systems. Recent research has identified two proof-theoretic features that…

Logic in Computer Science · Computer Science 2008-04-14 Andrew Gacek , Dale Miller , Gopalan Nadathur

Standard belief change assumes an underlying logic containing full classical propositional logic. However, there are good reasons for considering belief change in less expressive logics as well. In this paper we build on recent…

Artificial Intelligence · Computer Science 2014-01-17 Richard Booth , Thomas Meyer , Ivan Varzinczak , Renata Wassermann

We study an extension of the Distributive Full Non-associative Lambek Calculus with iterative division operators. The iterative operators can be seen as representing iterative composition of linguistic resources or of actions. A complete…

Logic in Computer Science · Computer Science 2019-10-28 Igor Sedlár

In this article, we study some new characterizations of primitive recursive functions based on restricted forms of primitive recursion, improving the pioneering work of R. M. Robinson and M. D. Gladstone in this area. We reduce certain…

Symbolic Computation · Computer Science 2014-05-28 Daniel E. Severin

The literal and the initial literal shuffle have been introduced to model the behavior of two synchronized processes. However, it is not possible to describe the synchronization of multiple processes. Furthermore, both restricted forms of…

Formal Languages and Automata Theory · Computer Science 2021-08-23 Stefan Hoffmann

Choice revision is a sort of non-prioritized multiple revision, in which the agent partially accepts the new information represented by a set of sentences. We investigate the construction of choice revision based on a new approach to belief…

Logic · Mathematics 2018-05-02 Li Zhang

An increasing amount of research in Natural Language Inference (NLI) focuses on the application and evaluation of Large Language Models (LLMs) and their reasoning capabilities. Despite their success, however, LLMs are still prone to factual…

Computation and Language · Computer Science 2024-02-02 Xin Quan , Marco Valentino , Louise A. Dennis , André Freitas

In this paper, several modifications are introduced to the functional approximation method iterLap to reduce the approximation error, including stopping rule adjustment, proposal of new residual function, starting point selection for…

Methodology · Statistics 2015-09-23 Tiep Mai , Simon Wilson

Our impression about one person often updates after we see more aspects of him/her and this process keeps iterating given more meetings. We formulate such an intuition into the problem of person re-identification (re-ID), where the…

Computer Vision and Pattern Recognition · Computer Science 2020-12-02 Dengpan Fu , Bo Xin , Jingdong Wang , Dongdong Chen , Jianmin Bao , Gang Hua , Houqiang Li

We introduce a generic presentation of 'syntactic objects built by mixed induction and coinduction' encompassing all standard kinds of infinitary terms, as well as derivation trees in non-wellfounded proof systems. We then define a notion…

Logic in Computer Science · Computer Science 2026-04-27 Rémy Cerda , Alexis Saurin

Many meta-learning approaches for few-shot learning rely on simple base learners such as nearest-neighbor classifiers. However, even in the few-shot regime, discriminatively trained linear predictors can offer better generalization. We…

Computer Vision and Pattern Recognition · Computer Science 2019-04-24 Kwonjoon Lee , Subhransu Maji , Avinash Ravichandran , Stefano Soatto

The paper proposes a new static analysis designed to handle open programs, i.e., fragments of programs, with dynamic pointer-linked data structures - in particular, various kinds of lists - that employ advanced low-level pointer operations.…

Logic in Computer Science · Computer Science 2022-05-06 Lukáš Holík , Petr Peringer , Adam Rogalewicz , Veronika Šoková , Tomáš Vojnar , Florian Zuleger

We present a new set of reductions for derivations in natural deduction that can extract witnesses from closed derivations of simply existential formulas in Heyting Arithmetic (HA) plus the Excluded Middle Law restricted to simply…

Logic · Mathematics 2013-05-16 Giovanni Birolo

Iterative regularization is a classic idea in regularization theory, that has recently become popular in machine learning. On the one hand, it allows to design efficient algorithms controlling at the same time numerical and statistical…

Machine Learning · Statistics 2024-10-10 Vassilis Apidopoulos , Tomaso Poggio , Lorenzo Rosasco , Silvia Villa

We consider an extension of bi-intuitionistic logic with the traditional modalities from tense logic Kt. Proof theoretically, this extension is obtained simply by extending an existing sequent calculus for bi-intuitionistic logic with…

Logic in Computer Science · Computer Science 2010-06-30 Rajeev Gore , Linda Postniece , Alwen Tiu

We develop the few-shot continual learning task from first principles and hypothesize an evolutionary motivation and mechanism of action for executive function as a contrastive value policy which resamples and relabels perception data via…

Computation and Language · Computer Science 2022-04-28 Chris Lengerich , Ben Lengerich

Due to the surprisingly good representation power of complex distributions, neural network (NN) classifiers are widely used in many tasks which include natural language processing, computer vision and cyber security. In recent works, people…

Machine Learning · Computer Science 2019-06-28 Guanxiong Liu , Issa Khalil , Abdallah Khreishah

In this paper we exploit Answer Set Programming (ASP) for reasoning in a rational extension SROEL-R-T of the low complexity description logic SROEL, which underlies the OWL EL ontology language. In the extended language, a typicality…

Artificial Intelligence · Computer Science 2016-08-09 Laura Giordano , Daniele Theseider Dupré

Referring object detection and referring image segmentation are important tasks that require joint understanding of visual information and natural language. Yet there has been evidence that current benchmark datasets suffer from bias, and…

Computer Vision and Pattern Recognition · Computer Science 2019-04-09 Runtao Liu , Chenxi Liu , Yutong Bai , Alan Yuille

Regularized empirical risk minimization with constrained labels (in contrast to fixed labels) is a remarkably general abstraction of learning. For common loss and regularization functions, this optimization problem assumes the form of a…

Machine Learning · Computer Science 2016-02-23 Iaroslav Shcherbatyi , Bjoern Andres
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