Search Results for author:
Found 12 papers, 3 papers with code
Spatial Clustering Approach for Vessel Path Identification
This paper addresses the challenge of identifying the paths for vessels with operating routes of repetitive paths, partially repetitive paths, and new paths.
Forecasting Auxiliary Energy Consumption for Electric Heavy-Duty Vehicles
Given that the employed groupings correspond to relevant sub-populations, the associations between the input features and the target values are consistent within each cluster but different across clusters.
Heterogeneous Federated Learning via Personalized Generative Networks
In this paper, we provide theoretical proof that minimizing heterogeneity between clients facilitates the convergence of a global model for every single client.
Explainable Predictive Maintenance
We provide an overview of predictive maintenance tasks and accentuate the need and varying purposes for corresponding explanations.
Explainable artificial intelligence
Explainable Artificial Intelligence (XAI)
Learning Causal Mechanisms through Orthogonal Neural Networks
Addressing this crucial discrepancy between human and machine intelligence is an important challenge for pattern recognition systems.
Information-Gathering in Latent Bandits
In the latent bandit problem, the learner has access to reward distributions and -- for the non-stationary variant -- transition models of the environment.
Wisdom of the Contexts: Active Ensemble Learning for Contextual Anomaly Detection
Furthermore, the results support our initial hypothesis that there is no single perfect context that successfully uncovers all kinds of contextual anomalies, and leveraging the "wisdom" of multiple contexts is necessary.
Pitfalls of Assessing Extracted Hierarchies for Multi-Class Classification
In these datasets, the right hierarchy can dramatically improve classification performance.
A New Bandit Setting Balancing Information from State Evolution and Corrupted Context
We present an algorithm that uses a referee to dynamically combine the policies of a contextual bandit and a multi-armed bandit.
No Free Lunch But A Cheaper Supper: A General Framework for Streaming Anomaly Detection
To date, there exists no single general method that has been shown to outperform the others across different anomaly types, use cases and datasets.
Machine learning in healthcare -- a system's perspective
Though the application of ML on health data have shown incremental improvements for clinical decision support, ML has a much a broader potential to restructure care delivery as a whole and maximize care value.
A data-driven approach for discovering heat load patterns in district heating
Understanding the heat usage of customers is crucial for effective district heating operations and management.
