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This article presents a pattern-based language designed to select (a set of) subterms of a given term in a concise and robust way. Building on this language, we implement a single-step rewriting tactic in the Isabelle theorem prover, which…

Logic in Computer Science · Computer Science 2021-11-09 Lars Noschinski , Christoph Traut

We present a deep generative model for unsupervised text style transfer that unifies previously proposed non-generative techniques. Our probabilistic approach models non-parallel data from two domains as a partially observed parallel…

Computation and Language · Computer Science 2020-05-01 Junxian He , Xinyi Wang , Graham Neubig , Taylor Berg-Kirkpatrick

Given a closed-source program, such as most of proprietary software and viruses, binary code analysis is indispensable for many tasks, such as code plagiarism detection and malware analysis. Today, source code is very often compiled for…

Cryptography and Security · Computer Science 2018-12-27 Kimberly Redmond , Lannan Luo , Qiang Zeng

A fundamental theme in automata theory is regular languages of words and trees, and their many equivalent definitions. Salvati has proposed a generalization to regular languages of simply typed $\lambda$-terms, defined using denotational…

Logic in Computer Science · Computer Science 2024-02-09 Vincent Moreau , Lê Thành Dũng Nguyên

We propose and analyze a regularization approach for structured prediction problems. We characterize a large class of loss functions that allows to naturally embed structured outputs in a linear space. We exploit this fact to design…

Machine Learning · Computer Science 2017-07-31 Carlo Ciliberto , Alessandro Rudi , Lorenzo Rosasco

We compare ordinary and symmetric variants of two classical measures of pseudorandomness for binary sequences, the $2$-adic complexity and the linear complexity. In the periodic setting, we show that for binary periodic sequences…

Number Theory · Mathematics 2026-03-25 Yixin Ren , Arne Winterhof

Recent research (arXiv:2310.11453, arXiv:2402.17764) has proposed binary and ternary transformer networks as a way to significantly reduce memory and improve inference speed in Large Language Models (LLMs) while maintaining accuracy. In…

Machine Learning · Computer Science 2024-05-29 Jason Li

We study the Lorentz and Dirac algebra, including antisymmetric $\epsilon$ tensors and the $\gamma_5$ matrix, in implicit gauge-invariant regularization/renormalization methods defined in fixed integer dimensions. They include constrained…

High Energy Physics - Phenomenology · Physics 2018-09-26 A. M. Bruque , A. L. Cherchiglia , M. Perez-Victoria

Natural language understanding systems struggle with low-resource languages, including many dialects of high-resource ones. Dialect-to-standard normalization attempts to tackle this issue by transforming dialectal text so that it can be…

Computation and Language · Computer Science 2025-06-11 Antonios Dimakis , John Pavlopoulos , Antonios Anastasopoulos

This paper studies normalisation by evaluation for typed lambda calculus from a categorical and algebraic viewpoint. The first part of the paper analyses the lambda definability result of Jung and Tiuryn via Kripke logical relations and…

Logic in Computer Science · Computer Science 2022-08-19 Marcelo Fiore

This paper presents new identities expressing the terms of Fibonacci, Lucas, and generalized Fibonacci sequences with multiple indices through powers of Lucas numbers and binomial coefficients. The obtained formulas rely on the application…

Combinatorics · Mathematics 2026-04-24 Nick Vorobtsov

There exist many high-dimensional data in real-world applications such as biology, computer vision, and social networks. Feature selection approaches are devised to confront with high-dimensional data challenges with the aim of efficient…

Machine Learning · Computer Science 2021-06-22 Mohsen Ghassemi Parsa , Hadi Zare , Mehdi Ghatee

An approach to (normalized) infinite dimensional integrals, including normalized oscillatory integrals, through a sequence of evaluations in the spirit of the Monte Carlo method for probability measures is proposed. in this approach the…

Mathematical Physics · Physics 2015-06-05 Jean-Pierre Magnot

Inspired by distributed algorithms, we introduce a new class of finite graph automata that recognize precisely the graph languages definable in monadic second-order logic. For the cases of words and trees, it has been long known that the…

Formal Languages and Automata Theory · Computer Science 2014-04-28 Fabian Reiter

A double occurrence word $w$ over a finite alphabet $\Sigma$ is a word in which each alphabet letter appears exactly twice. Such words arise naturally in the study of topology, graph theory, and combinatorics. Recently, double occurrence…

Combinatorics · Mathematics 2012-05-01 Jonathan Burns , Tilahun Muche

Many binary classification problems minimize misclassification above (or below) a threshold. We show that instances of ranking problems, accuracy at the top or hypothesis testing may be written in this form. We propose a general framework…

Machine Learning · Computer Science 2020-02-26 Lukáš Adam , Václav Mácha , Václav Šmídl , Tomáš Pevný

Tabular Language Models (TLMs) have been claimed to achieve emergent generalization for tabular prediction. We conduct a systematic re-evaluation of Tabula-8B as a representative TLM, utilizing 165 datasets from the UniPredict benchmark.…

Machine Learning · Computer Science 2026-02-05 Aditya Gorla , Ratish Puduppully

Most existing methods for automatic bilingual dictionary induction rely on prior alignments between the source and target languages, such as parallel corpora or seed dictionaries. For many language pairs, such supervised alignments are not…

Computation and Language · Computer Science 2018-03-26 Hanan Aldarmaki , Mahesh Mohan , Mona Diab

We extend the two-variable logic on data words with guarded regular binary predicates of the form $\widetilde{L}(x,y)$ that is true if positions $x$ and $y$ are in the same class and the factor strictly between $x$ and $y$ is in the regular…

Logic in Computer Science · Computer Science 2026-05-12 Shibashis Guha , Amaldev Manuel , S P Rishal

Low rank approximation is a commonly occurring problem in many computer vision and machine learning applications. There are two common ways of optimizing the resulting models. Either the set of matrices with a given rank can be explicitly…

Computer Vision and Pattern Recognition · Computer Science 2019-07-24 Marcus Valtonen Örnhag , Carl Olsson , Anders Heyden