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