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An occurrence of a repeated substring $u$ in a string $S$ is called a net occurrence if extending the occurrence to the left or to the right decreases the number of occurrences to 1. The net frequency (NF) of a repeated substring $u$ in a…

Data Structures and Algorithms · Computer Science 2026-01-01 Shunsuke Inenaga

Combining the representations of the words that make up a sentence into a cohesive whole is difficult, since it needs to account for the order of words, and to establish how the words present relate to each other. The solution we propose…

Computation and Language · Computer Science 2021-03-04 Diego Maupomé , Marie-Jean Meurs

The Subset Sum Problem is a fundamental NP-complete problem in cryptography and combinatorial optimization, with many real-world applications. The Random Subset Sum Problem (RSSP) is a more applicable version of subset sum, where numbers…

Data Structures and Algorithms · Computer Science 2026-05-21 Edwin Chen , Christof Teuscher

We consider the problem of finding repetitive structures and inherent patterns in a given string $\s{s}$ of length $n$ over a finite totally ordered alphabet. A border $\s{u}$ of a string $\s{s}$ is both a prefix and a suffix of $\s{s}$…

Data Structures and Algorithms · Computer Science 2015-06-24 Ali Alatabbi , Jacqueline W. Daykin , M. Sohel Rahman

The existing machine learning algorithms for minimizing the convex function over a closed convex set suffer from slow convergence because their learning rates must be determined before running them. This paper proposes two machine learning…

Optimization and Control · Mathematics 2019-09-02 Kazuhiro Hishinuma , Hideaki Iiduka

Sparse reduced rank regression is an essential statistical learning method. In the contemporary literature, estimation is typically formulated as a nonconvex optimization that often yields to a local optimum in numerical computation. Yet,…

Methodology · Statistics 2022-12-06 Canhong Wen , Ruipeng Dong , Xueqin Wang , Weiyu Li , Heping Zhang

Inverse Probability Weighting (IPW) is widely used in empirical work in economics and other disciplines. As Gaussian approximations perform poorly in the presence of "small denominators," trimming is routinely employed as a regularization…

Econometrics · Economics 2019-05-28 Xinwei Ma , Jingshen Wang

The theory of reinforcement learning has focused on two fundamental problems: achieving low regret, and identifying $\epsilon$-optimal policies. While a simple reduction allows one to apply a low-regret algorithm to obtain an…

Machine Learning · Computer Science 2022-06-23 Andrew Wagenmaker , Max Simchowitz , Kevin Jamieson

A string is said to be closed if its length is one, or if it has a non-empty factor that occurs both as a prefix and as a suffix of the string, but does not occur elsewhere. The notion of closed words was introduced by [Fici, WORDS 2011].…

Data Structures and Algorithms · Computer Science 2024-10-01 Takuya Mieno , Shun Takahashi , Kazuhisa Seto , Takashi Horiyama

Retrieval-Augmented Generation (RAG) has recently emerged as a method to extend beyond the pre-trained knowledge of Large Language Models by augmenting the original prompt with relevant passages or documents retrieved by an Information…

We construct fast algorithms for evaluating transforms associated with families of functions which satisfy recurrence relations. These include algorithms both for computing the coefficients in linear combinations of the functions, given the…

Computational Engineering, Finance, and Science · Computer Science 2025-10-20 Mark Tygert

In the problem of online unweighted interval selection, the objective is to maximize the number of non-conflicting intervals accepted by the algorithm. In the conventional online model of irrevocable decisions, there is an Omega(n) lower…

Data Structures and Algorithms · Computer Science 2025-06-03 Allan Borodin , Christodoulos Karavasilis

Importance sampling (IS) is a common reweighting strategy for off-policy prediction in reinforcement learning. While it is consistent and unbiased, it can result in high variance updates to the weights for the value function. In this work,…

Machine Learning · Computer Science 2019-11-15 Matthew Schlegel , Wesley Chung , Daniel Graves , Jian Qian , Martha White

The problem of word sense disambiguation (WSD) is considered in the article. Given a set of synonyms (synsets) and sentences with these synonyms. It is necessary to select the meaning of the word in the sentence automatically. 1285…

Information Retrieval · Computer Science 2018-07-12 Alexander Kirillov , Natalia Krizhanovsky , Andrew Krizhanovsky

In real-time speech recognition applications, the latency is an important issue. We have developed a character-level incremental speech recognition (ISR) system that responds quickly even during the speech, where the hypotheses are…

Computation and Language · Computer Science 2016-06-29 Kyuyeon Hwang , Wonyong Sung

In this paper, we explore worst-case solutions for the problems of single and multiple matching on strings in the word RAM model with word length w. In the first problem, we have to build a data structure based on a pattern p of length m…

Data Structures and Algorithms · Computer Science 2015-05-20 Djamal Belazzougui

Estimating the expectations of functionals applied to sums of random variables (RVs) is a well-known problem encountered in many challenging applications. Generally, closed-form expressions of these quantities are out of reach. A naive…

Information Theory · Computer Science 2022-10-27 Eya Ben Amar , Nadhir Ben Rached , Abdul-Lateef Haji-Ali , Raúl Tempone

We study the problems of finding a shortest synchronizing word and its length for a given prefix code. This is done in two different settings: when the code is defined by an arbitrary decoder recognizing its star and when the code is…

Formal Languages and Automata Theory · Computer Science 2018-06-19 Andrew Ryzhikov , Marek Szykuła

We study a variation of the classical Shortest Common Superstring (SCS) problem in which a shortest superstring of a finite set of strings $S$ is sought containing as a factor every string of $S$ or its reversal. We call this problem…

Data Structures and Algorithms · Computer Science 2015-12-08 Gabriele Fici , Tomasz Kociumaka , Jakub Radoszewski , Wojciech Rytter , Tomasz Waleń

Polynomial time reductions between problems have long been used to delineate problem classes. Simulation reductions also exist, where an oracle for simulation from some probability distribution can be employed together with an oracle for…

Probability · Mathematics 2009-08-18 Mark L. Huber