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Found 8 papers, 3 papers with code
OneShotSTL: One-Shot Seasonal-Trend Decomposition For Online Time Series Anomaly Detection And Forecasting
Extensive experiments on real-world benchmark datasets for downstream time series anomaly detection and forecasting tasks demonstrate that OneShotSTL is from 10 to over 1, 000 times faster than the state-of-the-art methods, while still providing comparable or even better accuracy.
A Unified and Efficient Coordinating Framework for Autonomous DBMS Tuning
To tune different components for DBMS, a coordinating mechanism is needed to make the multiple agents cognizant of each other.
Interactive Log Parsing via Light-weight User Feedback
Template mining is one of the foundational tasks to support log analysis, which supports the diagnosis and troubleshooting of large scale Web applications.
LPC-AD: Fast and Accurate Multivariate Time Series Anomaly Detection via Latent Predictive Coding
LPC-AD is motivated by the ever-increasing needs for fast and accurate MTS anomaly detection methods to support fast troubleshooting in cloud computing, micro-service systems, etc.
CobBO: Coordinate Backoff Bayesian Optimization with Two-Stage Kernels
These virtual points, along with the means and variances of their unknown function values estimated using the simple kernel of the first stage, are fitted to a more sophisticated kernel model in the second stage.
Local Differential Privacy for Bayesian Optimization
Motivated by the increasing concern about privacy in nowadays data-intensive online learning systems, we consider a black-box optimization in the nonparametric Gaussian process setting with local differential privacy (LDP) guarantee.
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 time series analysis like forecasting and anomaly detection.
Learning Latent Features with Pairwise Penalties in Low-Rank Matrix Completion
Low-rank matrix completion has achieved great success in many real-world data applications.
