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Random access to highly compressed strings -- represented by straight-line programs or Lempel-Ziv parses, for example -- is a well-studied topic. Random access to such strings in strongly sublogarithmic time is impossible in the worst case,…

Data Structures and Algorithms · Computer Science 2026-02-05 Ferdinando Cicalese , Zsuzsanna Lipták , Travis Gagie , Gonzalo Navarro , Nicola Prezza , Cristian Urbina

The capabilities of Large Language Models (LLMs) have significantly evolved, extending from natural language processing to complex tasks like code understanding and generation. We expand the scope of LLMs' capabilities to a broader context,…

Computation and Language · Computer Science 2024-10-11 Chenyang Lyu , Lecheng Yan , Rui Xing , Wenxi Li , Younes Samih , Tianbo Ji , Longyue Wang

Global SLS-resolution and SLG-resolution are two representative mechanisms for top-down evaluation of the well-founded semantics of general logic programs. Global SLS-resolution is linear for query evaluation but suffers from infinite loops…

Artificial Intelligence · Computer Science 2007-05-23 Yi-Dong Shen , Li-Yan Yuan , Jia-Huai You

Lagrangian Relaxation (LR) is a powerful technique for solving large-scale Mixed Integer Linear Programming (MILP), particularly those with decomposable structures, such as vehicle routing or unit commitment problems. By relaxing the…

Machine Learning · Statistics 2026-05-27 Tung Quoc Le , Anh Tuan Nguyen , Viet Anh Nguyen

We present a highly parallelizable text compression algorithm that scales efficiently to terabyte-sized datasets. Our method builds on locally consistent grammars, a lightweight form of compression, combined with simple recompression…

Data Structures and Algorithms · Computer Science 2025-02-26 Diego Diaz-Dominguez

We propose a new exact approach for solving integer linear programming (ILP) problems which we will call projective splitting algorithms (PSAs). Unlike classical methods for solving ILP problems, PSAs conduct the search for the optimal…

Optimization and Control · Mathematics 2014-04-16 Federico Rodes , Isabel Mendez-Diaz , Paula Zabala

Large Language Models (LLMs) struggle with reliably generating highly structured outputs, such as program code, mathematical formulas, or well-formed markup. Constrained decoding approaches mitigate this problem by greedily restricting what…

Artificial Intelligence · Computer Science 2025-12-15 Kanghee Park , Jiayu Wang , Taylor Berg-Kirkpatrick , Nadia Polikarpova , Loris D'Antoni

Osborne's iteration is a method for balancing $n\times n$ matrices which is widely used in linear algebra packages, as balancing preserves eigenvalues and stabilizes their numeral computation. The iteration can be implemented in any norm…

Data Structures and Algorithms · Computer Science 2017-04-26 Rafail Ostrovsky , Yuval Rabani , Arman Yousefi

The most fundamental problem considered in algorithms for text processing is pattern matching: given a pattern $p$ of length $m$ and a text $t$ of length $n$, does $p$ occur in $t$? Multiple versions of this basic question have been…

Data Structures and Algorithms · Computer Science 2021-11-10 Moses Ganardi , Paweł Gawrychowski

It is shown that a context-free grammar of size $m$ that produces a single string $w$ (such a grammar is also called a string straight-line program) can be transformed in linear time into a context-free grammar for $w$ of size…

Data Structures and Algorithms · Computer Science 2020-07-02 Moses Ganardi , Artur Jeż , Markus Lohrey

Longest common substring (LCS), longest palindrome substring (LPS), and Ulam distance (UL) are three fundamental string problems that can be classically solved in near linear time. In this work, we present sublinear time quantum algorithms…

Quantum Physics · Physics 2023-12-29 François Le Gall , Saeed Seddighin

Large Language Models (LLMs), originally developed for natural language processing (NLP), have demonstrated the potential to generalize across modalities and domains. With their in-context learning (ICL) capabilities, LLMs can perform…

Artificial Intelligence · Computer Science 2025-08-26 Nikolaos Pavlidis , Vasilis Perifanis , Symeon Symeonidis , Pavlos S. Efraimidis

Given the success of Large Language Models (LLMs), there has been considerable interest in studying the properties of model activations. The literature overwhelmingly agrees that LLM representations are dominated by a few "outlier…

Computation and Language · Computer Science 2024-04-05 William Rudman , Carsten Eickhoff

Probabilistic Logic Programs (PLPs) generalize traditional logic programs and allow the encoding of models combining logical structure and uncertainty. In PLP, inference is performed by summarizing the possible worlds which entail the query…

Logic in Computer Science · Computer Science 2018-04-30 Arun Nampally , Timothy Zhang , C. R. Ramakrishnan

(We apologize for pidgin LaTeX) Schlipf \cite{sch91} proved that Stable Logic Programming (SLP) solves all $\mathit{NP}$ decision problems. We extend Schlipf's result to prove that SLP solves all search problems in the class $\mathit{NP}$.…

Artificial Intelligence · Computer Science 2007-05-23 Victor W. Marek , Jeffrey B. Remmel

In the problem of $\texttt{Generalised Pattern Matching}\ (\texttt{GPM})$ [STOC'94, Muthukrishnan and Palem], we are given a text $T$ of length $n$ over an alphabet $\Sigma_T$, a pattern $P$ of length $m$ over an alphabet $\Sigma_P$, and a…

Data Structures and Algorithms · Computer Science 2020-01-20 Bartłomiej Dudek , Paweł Gawrychowski , Tatiana Starikovskaya

There is always a natural embedding of $S_s\wr S_k$ into the linear programming (LP) relaxation permutation symmetry group of an orthogonal array integer linear programming (ILP) formulation with equality constraints. The point of this…

Optimization and Control · Mathematics 2021-04-23 David M. Arquette , Dursun A. Bulutoglu

This article presents a numerical illustration of a recently proposed strongly polynomial-time algorithm for the general linear programming (LP) problem. Each iteration of the proposed algorithm consists of two Gauss-Jordan pivoting…

Optimization and Control · Mathematics 2026-05-12 Samuel Awoniyi

Mixed integer nonlinear programming (MINLP) problems are encountered in modeling a physical/industrial process consisting both nonlinearity and discrete selective parameters. There are variety of algorithms for solving MINLP problems most…

Optimization and Control · Mathematics 2024-05-17 Negin Bagherpour , Mahdi Sharifzadeh

The Karp-Rabin fingerprint of a string is a type of hash value that due to its strong properties has been used in many string algorithms. In this paper we show how to construct a data structure for a string $S$ of size $N$ compressed by a…

Data Structures and Algorithms · Computer Science 2013-05-17 Philip Bille , Patrick Hagge Cording , Inge Li Gørtz , Benjamin Sach , Hjalte Wedel Vildhøj , Søren Vind