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A longest common extension (LCE) query on a string computes the length of the longest common suffix or prefix at two given positions. A dynamic LCE algorithm maintains a data structure that allows efficient LCE queries on a string that can…

Data Structures and Algorithms · Computer Science 2026-04-15 Daniel Albert

Suffix sort plays a critical role in various computational algorithms including genomics as well as in frequently used day to day software applications. The sorting algorithm becomes tricky when we have lot of repeated characters in the…

Data Structures and Algorithms · Computer Science 2022-10-05 Kunal Chowdhury

In a large-scale and distributed matrix multiplication problem $C=A^{\intercal}B$, where $C\in\mathbb{R}^{r\times t}$, the coded computation plays an important role to effectively deal with "stragglers" (distributed computations that may…

Distributed, Parallel, and Cluster Computing · Computer Science 2018-04-19 Sinong Wang , Jiashang Liu , Ness Shroff

The sparse factorization of a large matrix is fundamental in modern statistical learning. In particular, the sparse singular value decomposition and its variants have been utilized in multivariate regression, factor analysis, biclustering,…

Machine Learning · Statistics 2020-03-19 Kun Chen , Ruipeng Dong , Wanwan Xu , Zemin Zheng

We revisit two well-known algorithmic problems on strings: computing a shortest unique substring (SUS) and a shortest absent substring (SAS) of a string $S$ of length $n$. Both problems admit folklore $\mathcal{O}(n)$-time solutions using…

Data Structures and Algorithms · Computer Science 2026-05-07 Panagiotis Charalampopoulos , Manal Mohamed , Solon P. Pissis , Hilde Verbeek , Wiktor Zuba

There are two major approaches for sequence labeling. One is the probabilistic gradient-based methods such as conditional random fields (CRF) and neural networks (e.g., RNN), which have high accuracy but drawbacks: slow training, and no…

Machine Learning · Computer Science 2018-11-20 Xu Sun , Shuming Ma , Yi Zhang , Xuancheng Ren

We present a comprehensive framework for structured sparse coding and modeling extending the recent ideas of using learnable fast regressors to approximate exact sparse codes. For this purpose, we develop a novel block-coordinate proximal…

Machine Learning · Computer Science 2012-06-22 Alex Bronstein , Pablo Sprechmann , Guillermo Sapiro

Efficient solutions of large-scale, ill-conditioned and indefinite algebraic equations are ubiquitously needed in numerous computational fields, including multiphysics simulations, machine learning, and data science. Because of their…

Mathematical Software · Computer Science 2026-05-25 Xiaoye Sherry Li , Yang Liu

It has been shown in the indexing literature that there is an essential difference between prefix/range searches on the one hand, and predecessor/rank searches on the other hand, in that the former provably allows faster query resolution.…

Data Structures and Algorithms · Computer Science 2018-04-16 Djamal Belazzougui , Paolo Boldi , Rasmus Pagh , Sebastiano Vigna

We propose a fast greedy algorithm to compute sparse representations of signals from continuous dictionaries that are factorizable, i.e., with atoms that can be separated as a product of sub-atoms. Existing algorithms strongly reduce the…

Signal Processing · Electrical Eng. & Systems 2020-12-01 Gilles Monnoyer de Galland , Luc Vandendorpe , Laurent Jacques

Sparse representation has been applied successfully in abnormal event detection, in which the baseline is to learn a dictionary accompanied by sparse codes. While much emphasis is put on discriminative dictionary construction, there are no…

Computer Vision and Pattern Recognition · Computer Science 2016-03-15 Huamin Ren , Hong Pan , Søren Ingvor Olsen , Thomas B. Moeslund

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

We present a new algorithm for finding a near optimal low-rank approximation of a matrix $A$ in $O(nnz(A))$ time. Our method is based on a recursive sampling scheme for computing a representative subset of $A$'s columns, which is then used…

Data Structures and Algorithms · Computer Science 2016-10-10 Michael B. Cohen , Cameron Musco , Christopher Musco

There has been significant interest and progress recently in algorithms that solve regression problems involving tall and thin matrices in input sparsity time. These algorithms find shorter equivalent of a n*d matrix where n >> d, which…

Data Structures and Algorithms · Computer Science 2013-04-05 Mu Li , Gary L. Miller , Richard Peng

In this paper, we consider a well-known sparse optimization problem that aims to find a sparse solution of a possibly noisy underdetermined system of linear equations. Mathematically, it can be modeled in a unified manner by minimizing…

Optimization and Control · Mathematics 2021-10-01 Lei Yang , Xiaojun Chen , Shuhuang Xiang

We revisit the classic combinatorial pattern matching problem of finding a longest common subsequence (LCS). For strings $x$ and $y$ of length $n$, a textbook algorithm solves LCS in time $O(n^2)$, but although much effort has been spent,…

Computational Complexity · Computer Science 2018-03-05 Karl Bringmann , Marvin Künnemann

We study the Sparse Plus Low-Rank decomposition problem (SLR), which is the problem of decomposing a corrupted data matrix into a sparse matrix of perturbations plus a low-rank matrix containing the ground truth. SLR is a fundamental…

Machine Learning · Statistics 2023-11-15 Dimitris Bertsimas , Ryan Cory-Wright , Nicholas A. G. Johnson

We propose a new approach for calculating the Lempel-Ziv factorization of a string, based on run length encoding (RLE). We present a conceptually simple off-line algorithm based on a variant of suffix arrays, as well as an on-line algorithm…

Data Structures and Algorithms · Computer Science 2015-03-20 Jun'ichi Yamamoto , Hideo Bannai , Shunsuke Inenaga , Masayuki Takeda

Compressive sensing aims to recover a high-dimensional sparse signal from a relatively small number of measurements. In this paper, a novel design of the measurement matrix is proposed. The design is inspired by the construction of…

Information Theory · Computer Science 2016-03-22 Xu Chen , Dongning Guo

This paper presents a general technique for optimally transforming any dynamic data structure that operates on atomic and indivisible keys by constant-time comparisons, into a data structure that handles unbounded-length keys whose…

Data Structures and Algorithms · Computer Science 2013-06-04 Amihood Amir , Gianni Franceschini , Roberto Grossi , Tsvi Kopelowitz , Moshe Lewenstein , Noa Lewenstein