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Citation recommendation is an important task to assist scholars in finding candidate literature to cite. Traditional studies focus on static models of recommending citations, which do not explicitly distinguish differences between papers…

Information Retrieval · Computer Science 2021-01-20 Shutian Ma , Heng Zhang , Chengzhi Zhang , Xiaozhong Liu

The elementary affine lambda-calculus was introduced as a polyvalent setting for implicit computational complexity, allowing for characterizations of polynomial time and hyperexponential time predicates. But these results rely on type…

Logic in Computer Science · Computer Science 2019-08-15 Lê Thành Dũng Nguyen

Counterfactual explanations emerge as a powerful approach in explainable AI, providing what-if scenarios that reveal how minimal changes to an input time series can alter the model's prediction. This work presents a survey of recent…

Machine Learning · Computer Science 2026-03-31 Udo Schlegel , Thomas Seidl

In topology recognition, each node of an anonymous network has to deterministically produce an isomorphic copy of the underlying graph, with all ports correctly marked. This task is usually unfeasible without any a priori information. Such…

Distributed, Parallel, and Cluster Computing · Computer Science 2016-01-25 Emanuele Guido Fusco , Andrzej Pelc , Rossella Petreschi

In this paper, we propose an implementation of temporal semantics which is suitable for inference problems. This implementation translates syntax trees to logical formulas, suitable for consumption by the Coq proof assistant. We support…

Computation and Language · Computer Science 2020-12-22 Jean-Philippe Bernardy , Stergios Chatzikyriakidis

We study the task, for a given language $L$, of enumerating the (generally infinite) sequence of its words, without repetitions, while bounding the delay between two consecutive words. To allow for delay bounds that do not depend on the…

Formal Languages and Automata Theory · Computer Science 2023-01-10 Antoine Amarilli , Mikaël Monet

This paper proposes a method of segmenting temporal data into ordered classes. It is based on mixture models and a discrete latent process, which enables to successively activates the classes. The classification can be performed by…

Machine Learning · Statistics 2013-12-30 Faicel Chamroukhi , Allou Samé , Gérard Govaert , Patrice Aknin

We develop a qualitative model of decision making with two aims: to describe how people make simple decisions and to enable computer programs to do the same. Current approaches based on Planning or Decisions Theory either ignore uncertainty…

Artificial Intelligence · Computer Science 2013-02-18 Blai Bonet , Hector Geffner

State-of-the-art models of lexical semantic change detection suffer from noise stemming from vector space alignment. We have empirically tested the Temporal Referencing method for lexical semantic change and show that, by avoiding…

Computation and Language · Computer Science 2020-07-23 Haim Dubossarsky , Simon Hengchen , Nina Tahmasebi , Dominik Schlechtweg

We show that for any $i > 0$, it is decidable, given a regular language, whether it is expressible in the $\Sigma_i[<]$ fragment of first-order logic FO[<]. This settles a question open since 1971. Our main technical result relies on the…

Formal Languages and Automata Theory · Computer Science 2025-02-03 Corentin Barloy , Michaël Cadilhac , Charles Paperman , Howard Straubing

We address the important theoretical question why a recurrent neural network with fixed weights can adaptively classify time-varied signals in the presence of additive noise and parametric perturbations. We provide a mathematical proof…

Optimization and Control · Mathematics 2007-05-24 Ivan Tyukin , Danil Prokhorov , Cees van Leeuwen

The present paper presents and proves a proposition concerning the time complexity of finite languages. It is shown herein, that for any finite language (a language for which the set of words composing it is finite) there is a Turing…

Computational Complexity · Computer Science 2007-05-23 Mircea Alexandru Popescu Moscu

This work focuses on top-k recommendation in domains where underlying data distribution shifts overtime. We propose to learn a time-dependent bias for each item over whatever existing recommendation engine. Such a bias learning process…

Information Retrieval · Computer Science 2015-11-10 Lei Tang

We continue our study of ordered context-free grammars, a grammar formalism that places an order on the parse trees produced by the corresponding context-free grammar. In particular, we simplify our previous definition of a derivation of a…

Formal Languages and Automata Theory · Computer Science 2023-09-19 Brink van der Merwe

As artificial intelligence (AI) systems play an increasingly prominent role in human decision-making, challenges surface in the realm of human-AI interactions. One challenge arises from the suboptimal AI policies due to the inadequate…

Machine Learning · Statistics 2024-03-22 Guanting Chen , Xiaocheng Li , Chunlin Sun , Hanzhao Wang

Humans and animals have the ability to reason and make predictions about different courses of action at many time scales. In reinforcement learning, option models (Sutton, Precup \& Singh, 1999; Precup, 2000) provide the framework for this…

Machine Learning · Computer Science 2021-08-09 Khimya Khetarpal , Zafarali Ahmed , Gheorghe Comanici , Doina Precup

Active learning of timed languages is concerned with the inference of timed automata from observed timed words. The agent can query for the membership of words in the target language, or propose a candidate model and verify its equivalence…

Logic in Computer Science · Computer Science 2020-07-09 Léo Henry , Nicolas Markey , Thierry Jéron

We show that strategies implemented in automatic theorem proving involve an interesting tradeoff between execution speed, proving speedup/computational time and usefulness of information. We advance formal definitions for these concepts by…

Logic in Computer Science · Computer Science 2015-06-16 Santiago Hernández-Orozco , Francisco Hernández-Quiroz , Hector Zenil , Wilfried Sieg

Constructor rewriting systems are said to be cons-free if, roughly, constructor terms in the right-hand sides of rules are subterms of the left-hand sides; the computational intuition is that rules cannot build new data structures. In…

Computational Complexity · Computer Science 2023-06-22 Cynthia Kop , Jakob Grue Simonsen

This paper introduces a class of objects called decision rules that map infinite sequences of alternatives to a decision space. These objects can be used to model situations where a decision maker encounters alternatives in a sequence such…

Theoretical Economics · Economics 2022-09-12 Bhavook Bhardwaj , Siddharth Chatterjee