61 citations · 66 across the 3 of their papers we have counts for
4 papers
Real-time Drift Detection on Time-series Data
Nandini Ramanan, Rasool Tahmasbi, Marjorie Sayer +3
Practical machine learning applications involving time series data, such as firewall log analysis to proactively detect anomalous behavior, are concerned with real time analysis of…
Time Series Anomaly Detection with label-free Model Selection
Deokwoo Jung, Nandini Ramanan, Mehrnaz Amjadi +3
Anomaly detection for time-series data becomes an essential task for many data-driven applications fueled with an abundance of data and out-of-the-box machine-learning algorithms.…
Boosted Embeddings for Time Series Forecasting
Sankeerth Rao Karingula, Nandini Ramanan, Rasool Tahmasbi +7
Time series forecasting is a fundamental task emerging from diverse data-driven applications. Many advanced autoregressive methods such as ARIMA were used to develop forecasting mo…
Semi-supervised Learning with Deep Generative Models for Asset Failure Prediction
Andre S. Yoon, Taehoon Lee, Yongsub Lim +5
This work presents a novel semi-supervised learning approach for data-driven modeling of asset failures when health status is only partially known in historical data. We combine a…