5 citations · 5 across the 6 of their papers we have counts for
5 papers · 1 filter
Contrastive Credibility Propagation for Reliable Semi-Supervised Learning
Brody Kutt, Pralay Ramteke, Xavier Mignot +6
Producing labels for unlabeled data is error-prone, making semi-supervised learning (SSL) troublesome. Often, little is known about when and why an algorithm fails to outperform a…
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…
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…