5 citations · 5 across the 4 of their papers we have counts for
6 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.…
Log2NS: Enhancing Deep Learning Based Analysis of Logs With Formal to Prevent Survivorship Bias
Charanraj Thimmisetty, Praveen Tiwari, Didac Gil de la Iglesia +4
Analysis of large observational data sets generated by a reactive system is a common challenge in debugging system failures and determining their root cause. One of the major probl…
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…
One-Shot Induction of Generalized Logical Concepts via Human Guidance
Mayukh Das, Nandini Ramanan, Janardhan Rao Doppa +1
We consider the problem of learning generalized first-order representations of concepts from a single example. To address this challenging problem, we augment an inductive logic pr…
Structure Learning for Relational Logistic Regression: An Ensemble Approach
Nandini Ramanan, Gautam Kunapuli, Tushar Khot +5
We consider the problem of learning Relational Logistic Regression (RLR). Unlike standard logistic regression, the features of RLRs are first-order formulae with associated weight…