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12/07/2022
Criteria for Classifying Forecasting Methods
Classifying forecasting methods as being either of a "machine learning" ...
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10/03/2022
Unsupervised Model Selection for Time-series Anomaly Detection
Anomaly detection in time-series has a wide range of practical applicati...
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05/31/2022
Robust Projection based Anomaly Extraction (RPE) in Univariate Time-Series
This paper presents a novel, closed-form, and data/computation efficient...
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02/23/2022
Testing Granger Non-Causality in Panels with Cross-Sectional Dependencies
This paper proposes a new approach for testing Granger non-causality on ...
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01/18/2022
Online Time Series Anomaly Detection with State Space Gaussian Processes
We propose r-ssGPFA, an unsupervised online anomaly detection model for ...
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12/06/2021
Online false discovery rate control for anomaly detection in time series
This article proposes novel rules for false discovery rate control (FDRC...
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06/21/2021
Spliced Binned-Pareto Distribution for Robust Modeling of Heavy-tailed Time Series
This work proposes a novel method to robustly and accurately model time ...
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09/15/2020
Improve black-box sequential anomaly detector relevancy with limited user feedback
Anomaly detectors are often designed to catch statistical anomalies. End...
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08/03/2020
A simple and effective predictive resource scaling heuristic for large-scale cloud applications
We propose a simple yet effective policy for the predictive auto-scaling...
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04/21/2020
Neural forecasting: Introduction and literature overview
Neural network based forecasting methods have become ubiquitous in large...
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10/07/2019
High-Dimensional Multivariate Forecasting with Low-Rank Gaussian Copula Processes
Predicting the dependencies between observations from multiple time seri...
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11/04/2014