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Large-scale deep learning models impose substantial communication overh ead in distributed training, particularly in bandwidth-constrained or heterogeneous clo ud-edge environments. Conventional synchronous or fixed-compression techniques o…

Distributed, Parallel, and Cluster Computing · Computer Science 2025-12-23 Yi Yang , Ziyu Lin , Liesheng Wei

Music can be represented in multiple forms, such as in the audio form as a recording of a performance, in the symbolic form as a computer readable score, or in the image form as a scan of the sheet music. Music synchronisation provides a…

Sound · Computer Science 2022-06-02 Ruchit Agrawal

Translating non-invasive signals such as photoplethysmography (PPG) and ballistocardiography (BCG) into clinically meaningful signals like arterial blood pressure (ABP) is vital for continuous, low-cost healthcare monitoring. However,…

Machine Learning · Computer Science 2025-11-27 Qian Hong , Cheng Bian , Xiao Zhou , Xiaoyu Li , Yelei Li , Zijing Zeng

Time-series forecasting is crucial for numerous real-world applications including weather prediction and financial market modeling. While temporal-domain methods remain prevalent, frequency-domain approaches can effectively capture…

Machine Learning · Computer Science 2025-08-05 Zhixuan Li , Naipeng Chen , Seonghwa Choi , Sanghoon Lee , Weisi Lin

The alignment of a set of objects by means of transformations plays an important role in computer vision. Whilst the case for only two objects can be solved globally, when multiple objects are considered usually iterative methods are used.…

Computer Vision and Pattern Recognition · Computer Science 2016-05-12 Florian Bernard , Johan Thunberg , Peter Gemmar , Frank Hertel , Andreas Husch , Jorge Goncalves

Today, people can easily record memorable moments, ranging from concerts, sports events, lectures, family gatherings, and birthday parties with multiple consumer cameras. However, synchronizing these cross-camera streams remains…

Computer Vision and Pattern Recognition · Computer Science 2025-12-02 Shaowei Liu , David Yifan Yao , Saurabh Gupta , Shenlong Wang

We introduce a dynamic approach to probabilistic forecast reconciliation at scale. Our model differs from the existing literature in this area in several important ways. Firstly we explicitly allow the weights allocated to the base…

Methodology · Statistics 2024-09-20 Ross Hollyman , Fotios Petropoulos , Michael E. Tipping

Many systems in our world age, degrade or otherwise move slowly but steadily in a certain direction. When monitoring such systems by means of sensors, one often assumes that some form of `age' is latently present in the data, but perhaps…

Machine Learning · Computer Science 2025-10-23 Guus Toussaint , Arno Knobbe

Time series is a special type of sequence data, a sequence of real-valued random variables collected at even intervals of time. The real-world multivariate time series comes with noises and contains complicated local and global temporal…

Machine Learning · Computer Science 2023-11-21 Site Mo , Haoxin Wang , Bixiong Li , Songhai Fan , Yuankai Wu , Xianggen Liu

Performance-score synchronization is an integral task in signal processing, which entails generating an accurate mapping between an audio recording of a performance and the corresponding musical score. Traditional synchronization methods…

Sound · Computer Science 2022-04-20 Ruchit Agrawal , Daniel Wolff , Simon Dixon

Many important geometric estimation problems take the form of synchronization over the special Euclidean group: estimate the values of a set of poses given a set of relative measurements between them. This problem is typically formulated as…

Robotics · Computer Science 2017-02-07 David M. Rosen , Luca Carlone , Afonso S. Bandeira , John J. Leonard

We propose a novel Bayesian approach to modelling nonlinear alignments of time series based on latent shared information. We apply the method to the real-world problem of finding common structure in the sensor data of wind turbines…

Machine Learning · Statistics 2018-05-24 Markus Kaiser , Clemens Otte , Thomas Runkler , Carl Henrik Ek

Bayesian inference is often implemented using approximations, which can yield interval estimates that are too narrow, not fully capturing the uncertainty in the posterior distribution. We address the question of how to adjust these…

Methodology · Statistics 2026-03-23 Tiffany Cai , Philip Greengard , Ben Goodrich , Andrew Gelman

We propose a simple method to measure synchronization and time delay patterns between signals. It is based on the relative timings of events in the time series, defined e.g. as local maxima. The degree of synchronization is obtained from…

Chaotic Dynamics · Physics 2007-05-23 R. Quian Quiroga , T. Kreuz , P. Grassberger

In this work, we propose a hybrid Bayesian approach towards clock offset and skew estimation, thereby synchronizing large scale networks. In particular, we demonstrate the advantage of Bayesian Recursive Filtering (BRF) in alleviating…

Systems and Control · Electrical Eng. & Systems 2020-04-21 Meysam Goodarzi , Darko Cvetkovski , Nebojsa Maletic , Jesus Gutierrez , Eckhard Grass

Data reconciliation in general, and filesystem synchronization in particular, lacks rigorous theoretical foundation. This paper presents, for the first time, a complete analysis of synchronization for two replicas of a theoretical…

Information Theory · Computer Science 2022-11-15 Elod P. Csirmaz , Laszlo Csirmaz

The matrix profile is an effective data mining tool that provides similarity join functionality for time series data. Users of the matrix profile can either join a time series with itself using intra-similarity join (i.e., self-join) or…

Databases · Computer Science 2023-11-07 Chin-Chia Michael Yeh , Yan Zheng , Junpeng Wang , Huiyuan Chen , Zhongfang Zhuang , Wei Zhang , Eamonn Keogh

We propose a novel formulation for phase synchronization -- the statistical problem of jointly estimating alignment angles from noisy pairwise comparisons -- as a nonconvex optimization problem that enforces consistency among the pairwise…

Information Theory · Computer Science 2019-05-15 Tingran Gao , Zhizhen Zhao

A common problem to signal processing are biases introduced by correlated noise. When quantifying time delays between two signals, mixed noise introduces a bias towards zero delay in conventional delay estimates based on the cross- or…

Signal Processing · Electrical Eng. & Systems 2025-06-02 Tin Jurhar , Franziska Pellegrini , Ana I. Nuñes del Toro , Tilman Stephani , Guido Nolte , Stefan Haufe

Analyzing data from paleoclimate archives such as tree rings or lake sediments offers the opportunity of inferring information on past climate variability. Often, such data sets are univariate and a proper reconstruction of the system's…

Data Analysis, Statistics and Probability · Physics 2018-08-29 Jaqueline Lekscha , Reik V. Donner