Multiple Instance Learning for Detecting Anomalies over Sequential Real-World Datasets

no code implementations • 4 Oct 2022 • Parastoo Kamranfar, David Lattanzi, Amarda Shehu, Daniel Barbará

The MIL-based formulation performs no worse than single instance learning on easy to moderate datasets and outperforms single-instance learning on more challenging datasets.

Anomaly Detection Multiple Instance Learning

Traffic Flow Forecasting with Maintenance Downtime via Multi-Channel Attention-Based Spatio-Temporal Graph Convolutional Networks

no code implementations • 4 Oct 2021 • Yuanjie Lu, Parastoo Kamranfar, David Lattanzi, Amarda Shehu

However, a key shortcoming of state-of-the-art methods is their inability to take into account information of various modalities, for instance the impact of maintenance downtime on traffic flows.

Management

Bridge type classification: supervised learning on a modified NBI dataset

no code implementations • 12 Feb 2018 • Achyuthan Jootoo, David Lattanzi

Supervised learning models were then trained and tested using 10-fold cross validation on data for each state.

Classification feature selection +2