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We propose a method to improve traditional character-based PPM text compression algorithms. Consider a text file as a sequence of alternating words and non-words, the basic idea of our algorithm is to encode non-words and prefixes of words…

Information Theory · Computer Science 2015-03-17 Yichuan Hu , Jianzhong , Zhang , Farooq Khan , Ying Li

The goal of grammar compression is to construct a small sized context free grammar which uniquely generates the input text data. Among grammar compression methods, RePair is known for its good practical compression performance. MR-RePair…

Data Structures and Algorithms · Computer Science 2019-10-31 Isamu Furuya

When eating spaghetti, one should have the sauce and noodles mixed instead of eating them separately. We argue that also in string solving, word equations and regular constraints are better mixed together than approached separately as in…

Logic in Computer Science · Computer Science 2022-12-06 František Blahoudek , Yu-Fang Chen , David Chocholatý , Vojtěch Havlena , Lukáš Holík , Ondřej Lengál , Juraj Síč

Compression of inverted lists with methods that support fast intersection operations is an active research topic. Most compression schemes rely on encoding differences between consecutive positions with techniques that favor small numbers.…

Information Retrieval · Computer Science 2009-11-18 Francisco Claude , Antonio Farina , Gonzalo Navarro

The popular Alternating Least Squares (ALS) algorithm for tensor decomposition is efficient and easy to implement, but often converges to poor local optima---particularly when the weights of the factors are non-uniform. We propose a…

Machine Learning · Computer Science 2017-09-26 Vatsal Sharan , Gregory Valiant

In memory-constrained algorithms we have read-only access to the input, and the number of additional variables is limited. In this paper we introduce the compressed stack technique, a method that allows to transform algorithms whose space…

Computational Geometry · Computer Science 2014-06-26 Luis Barba , Matias Korman , Stefan Langerman , Kunikiko Sadakane , Rodrigo Silveira

We study distributed computing of the truncated singular value decomposition problem. We develop an algorithm that we call \texttt{LocalPower} for improving communication efficiency. Specifically, we uniformly partition the dataset among…

Machine Learning · Statistics 2021-06-07 Xiang Li , Shusen Wang , Kun Chen , Zhihua Zhang

In distribution compression, one aims to accurately summarize a probability distribution $\mathbb{P}$ using a small number of representative points. Near-optimal thinning procedures achieve this goal by sampling $n$ points from a Markov…

Machine Learning · Statistics 2022-10-19 Abhishek Shetty , Raaz Dwivedi , Lester Mackey

We present a new algorithm for subsequence matching in grammar compressed strings. Given a grammar of size $n$ compressing a string of size $N$ and a pattern string of size $m$ over an alphabet of size $\sigma$, our algorithm uses…

Data Structures and Algorithms · Computer Science 2014-06-06 Philip Bille , Patrick Hagge Cording , Inge Li Gørtz

In this work we introduce a new linear time compression algorithm, called "Re-pair for Trees", which compresses ranked ordered trees using linear straight-line context-free tree grammars. Such grammars generalize straight-line context-free…

Data Structures and Algorithms · Computer Science 2010-08-02 Markus Lohrey , Sebastian Maneth , Roy Mennicke

A simple linear-time algorithm for constructing a linear context-free tree grammar of size O(rg + r g log (n/r g))for a given input tree T of size n is presented, where g is the size of a minimal linear context-free tree grammar for T, and…

Data Structures and Algorithms · Computer Science 2018-10-09 Artur Jeż , Markus Lohrey

We consider two kinds of problems: the computation of polynomial and rational solutions of linear recurrences with coefficients that are polynomials with integer coefficients; indefinite and definite summation of sequences that are…

Symbolic Computation · Computer Science 2008-04-03 Alin Bostan , Frédéric Chyzak , Bruno Salvy , Thomas Cluzeau

The idea that many important classes of signals can be well-represented by linear combinations of a small set of atoms selected from a given dictionary has had dramatic impact on the theory and practice of signal processing. For practical…

Information Theory · Computer Science 2015-03-18 Quan Geng , Huan Wang , John Wright

We develop a new tool, namely polynomial and linear algebraic methods, for studying systems of word equations. We illustrate its usefulness by giving essentially simpler proofs of several hard problems. At the same time we prove extensions…

Combinatorics · Mathematics 2015-02-10 Aleksi Saarela

The aim of this paper is to provide several novel upper bounds on the excess risk with a primal focus on classification problems. We suggest two approaches and the obtained bounds are represented via the distribution dependent local…

Statistics Theory · Mathematics 2018-03-13 Nikita Zhivotovskiy

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

In this paper, we present a low-diameter decomposition algorithm in the LOCAL model of distributed computing that succeeds with probability $1 - 1/poly(n)$. Specifically, we show how to compute an $\left(\epsilon, O\left(\frac{\log…

Data Structures and Algorithms · Computer Science 2023-07-25 Yi-Jun Chang , Zeyong Li

We present an efficient algorithm for computing the LZ78 factorization of a text, where the text is represented as a straight line program (SLP), which is a context free grammar in the Chomsky normal form that generates a single string.…

Data Structures and Algorithms · Computer Science 2013-05-27 Hideo Bannai , Shunsuke Inenaga , Masayuki Takeda

The prohibitive sizes of Large Language Models (LLMs) today make it difficult to deploy them on memory-constrained edge devices. This work introduces $\rm CALDERA$ -- a new post-training LLM compression algorithm that harnesses the inherent…

Machine Learning · Computer Science 2024-11-05 Rajarshi Saha , Naomi Sagan , Varun Srivastava , Andrea J. Goldsmith , Mert Pilanci

This work proposes a discretization of the acoustic wave equation with possibly oscillatory coefficients based on a superposition of discrete solutions to spatially localized subproblems computed with an implicit time discretization. Based…

Numerical Analysis · Mathematics 2024-03-11 Dietmar Gallistl , Roland Maier