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Many real-world applications require aligning two temporal sequences, including bioinformatics, handwriting recognition, activity recognition, and human-robot coordination. Dynamic Time Warping (DTW) is a popular alignment method, but can…

Machine Learning · Computer Science 2021-09-21 Sridhar Mahadevan , Anup Rao , Georgios Theocharous , Jennifer Healey

Time Series Classification (TSC) is an important problem with numerous applications in science and technology. Dissimilarity-based approaches, such as Dynamic Time Warping (DTW), are classical methods for distinguishing time series when…

The proliferation and ubiquity of temporal data across many disciplines has sparked interest for similarity, classification and clustering methods specifically designed to handle time series data. A core issue when dealing with time series…

Machine Learning · Computer Science 2023-09-26 Iñigo Martinez

Temporal alignment of sequences is a fundamental challenge in many applications, such as computer vision and bioinformatics, where local time shifting needs to be accounted for. Misalignment can lead to poor model generalization, especially…

Machine Learning · Computer Science 2025-01-10 Afek Steinberg , Ran Eisenberg , Ofir Lindenbaum

The goal of temporal alignment is to establish time correspondence between two sequences, which has many applications in a variety of areas such as speech processing, bioinformatics, computer vision, and computer graphics. In this paper, we…

Machine Learning · Statistics 2012-06-20 Makoto Yamada , Leonid Sigal , Michalis Raptis , Masashi Sugiyama

String Edit Distance is a more-than-classical problem whose behavior in the dynamic setting, where the strings are updated over time, is well studied. A single-character substitution, insertion, or deletion can be processed in time…

Data Structures and Algorithms · Computer Science 2025-11-18 Bingbing Hu , Jakob Nogler , Barna Saha

Nearest neighbor search under elastic distances is a key tool for time series analysis, supporting many applications. However, straightforward implementations of distances require $O(n^2)$ space and time complexities, preventing these…

Machine Learning · Computer Science 2021-06-04 Matthieu Herrmann , Geoffrey I. Webb

The edit distance between two strings is defined as the smallest number of insertions, deletions, and substitutions that need to be made to transform one of the strings to another one. Approximating edit distance in subquadratic time is…

Data Structures and Algorithms · Computer Science 2018-04-27 Mahdi Boroujeni , Soheil Ehsani , Mohammad Ghodsi , MohammadTaghi HajiAghayi , Saeed Seddighin

The edit distance between two rooted ordered trees with $n$ nodes labeled from an alphabet~$\Sigma$ is the minimum cost of transforming one tree into the other by a sequence of elementary operations consisting of deleting and relabeling…

Data Structures and Algorithms · Computer Science 2017-03-28 Karl Bringmann , Paweł Gawrychowski , Shay Mozes , Oren Weimann

We present the first dynamic algorithms for Dyck and tree edit distances with subpolynomial update times. Dyck edit distance measures how far a parenthesis string is from a well-parenthesized expression, while tree edit distance quantifies…

Data Structures and Algorithms · Computer Science 2025-10-21 Debarati Das , Jacob Gilbert , MohammadTaghi Hajiaghayi , Tomasz Kociumaka , Barna Saha

We introduce the combinatorial optimization problem Time Disjoint Walks (TDW), which has applications in collision-free routing of discrete objects (e.g., autonomous vehicles) over a network. This problem takes as input a digraph $G$ with…

Data Structures and Algorithms · Computer Science 2020-02-19 Alexandre Bayen , Jesse Goodman , Eugene Vinitsky

Measuring distance or similarity between time-series data is a fundamental aspect of many applications including classification, clustering, and ensembling/alignment. Existing measures may fail to capture similarities among local trends…

Machine Learning · Computer Science 2024-12-20 Ajitesh Srivastava

Classic similarity measures of strings are longest common subsequence and Levenshtein distance (i.e., the classic edit distance). A classic similarity measure of curves is dynamic time warping. These measures can be computed by simple…

Computational Complexity · Computer Science 2015-04-06 Karl Bringmann , Marvin Künnemann

We address weakly supervised action alignment and segmentation in videos, where only the order of occurring actions is available during training. We propose Discriminative Differentiable Dynamic Time Warping (D3TW), the first discriminative…

Computer Vision and Pattern Recognition · Computer Science 2019-04-15 Chien-Yi Chang , De-An Huang , Yanan Sui , Li Fei-Fei , Juan Carlos Niebles

The min-distance between two nodes $u, v$ is defined as the minimum of the distance from $v$ to $u$ or from $u$ to $v$, and is a natural distance metric in DAGs. As with the standard distance problems, the Strong Exponential Time Hypothesis…

Data Structures and Algorithms · Computer Science 2022-10-05 Mina Dalirrooyfard , Jenny Kaufmann

The edit distance of two strings is the minimum number of insertions, deletions, and substitutions needed to transform one string into the other. The textbook algorithm determines the edit distance of length-$n$ strings in $O(n^2)$ time,…

Data Structures and Algorithms · Computer Science 2025-02-04 Egor Gorbachev , Tomasz Kociumaka

We offer to apply the powerful Dynamic Time Warping (DTW) algorithm to find the spreading rate variation by comparing profiles of marine magnetic anomalies with the synthetic field constructed by the magnetic polarity reference scale. For…

Geophysics · Physics 2017-12-12 S. A. Ivanov , S. A. Merkuriev

The edit distance is a way of quantifying how similar two strings are to one another by counting the minimum number of character insertions, deletions, and substitutions required to transform one string into the other. A simple dynamic…

Computational Complexity · Computer Science 2019-10-03 Elazar Goldenberg , Robert Krauthgamer , Barna Saha

Among many existing distance measures for time series data, Dynamic Time Warping (DTW) distance has been recognized as one of the most accurate and suitable distance measures due to its flexibility in sequence alignment. However, DTW…

Databases · Computer Science 2009-06-16 Vit Niennattrakul , Pongsakorn Ruengronghirunya , Chotirat Ann Ratanamahatana

Dynamic Threshold Optimization (DTO) adaptively "compresses" the decision space (DS) in a global search and optimization problem by bounding the objective function from below. This approach is different from "shrinking" DS by reducing…

Other Computer Science · Computer Science 2012-06-07 Richard A. Formato
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