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08/28/2023
BayOTIDE: Bayesian Online Multivariate Time series Imputation with functional decomposition
In real-world scenarios like traffic and energy, massive time-series dat...
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07/14/2023
Benchmarks and Custom Package for Electrical Load Forecasting
Load forecasting is of great significance in the power industry as it ca...
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07/07/2023
A Survey on Graph Neural Networks for Time Series: Forecasting, Classification, Imputation, and Anomaly Detection
Time series are the primary data type used to record dynamic system meas...
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06/17/2023
DCdetector: Dual Attention Contrastive Representation Learning for Time Series Anomaly Detection
Time series anomaly detection is critical for a wide range of applicatio...
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06/14/2023
SaDI: A Self-adaptive Decomposed Interpretable Framework for Electric Load Forecasting under Extreme Events
Accurate prediction of electric load is crucial in power grid planning a...
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05/31/2023
DiffLoad: Uncertainty Quantification in Load Forecasting with Diffusion Model
Electrical load forecasting is of great significance for the decision ma...
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03/07/2023
AHPA: Adaptive Horizontal Pod Autoscaling Systems on Alibaba Cloud Container Service for Kubernetes
The existing resource allocation policy for application instances in Kub...
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03/06/2023
Robust Dominant Periodicity Detection for Time Series with Missing Data
Periodicity detection is an important task in time series analysis, but ...
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11/29/2022
AirFormer: Predicting Nationwide Air Quality in China with Transformers
Air pollution is a crucial issue affecting human health and livelihoods,...
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10/24/2022
Towards Out-of-Distribution Sequential Event Prediction: A Causal Treatment
The goal of sequential event prediction is to estimate the next event ba...
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10/18/2022
TFAD: A Decomposition Time Series Anomaly Detection Architecture with Time-Frequency Analysis
Time series anomaly detection is a challenging problem due to the comple...
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06/07/2022
Robust Time Series Dissimilarity Measure for Outlier Detection and Periodicity Detection
Dynamic time warping (DTW) is an effective dissimilarity measure in many...
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04/14/2022
RobustScaler: QoS-Aware Autoscaling for Complex Workloads
Autoscaling is a critical component for efficient resource utilization w...
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02/23/2022
NetRCA: An Effective Network Fault Cause Localization Algorithm
Localizing the root cause of network faults is crucial to network operat...
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02/15/2022
Transformers in Time Series: A Survey
Transformers have achieved superior performances in many tasks in natura...
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11/05/2021
CloudRCA: A Root Cause Analysis Framework for Cloud Computing Platforms
As business of Alibaba expands across the world among various industries...
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03/03/2021
Two-Stage Framework for Seasonal Time Series Forecasting
Seasonal time series Forecasting remains a challenging problem due to th...
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02/27/2020
Time Series Data Augmentation for Deep Learning: A Survey
Deep learning performs remarkably well on many time series analysis task...
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02/21/2020
RobustTAD: Robust Time Series Anomaly Detection via Decomposition and Convolutional Neural Networks
The monitoring and management of numerous and diverse time series data a...
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02/21/2020
RobustPeriod: Time-Frequency Mining for Robust Multiple Periodicities Detection
Periodicity detection is an important task in time series analysis as it...
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06/10/2019
RobustTrend: A Huber Loss with a Combined First and Second Order Difference Regularization for Time Series Trend Filtering
Extracting the underlying trend signal is a crucial step to facilitate t...
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12/05/2018
