6 papers
Multi-Agent Conformal Prediction with Personalized Statistical Validity
Martin V. Vejling, Christophe A. N. Biscio, Adrien Mazoyer +2
Uncertainty quantification is essential in high-stakes machine learning tasks. However, one of the principled solutions, conformal prediction, faces challenges under limited local…
Online Continual Learning for Anomaly Detection in IoT under Data Distribution Shifts
Matea Marinova, Shashi Raj Pandey, Junya Shiraishi +3
In this work, we present OCLADS, a novel communication framework with continual learning (CL) for Internet of Things (IoT) anomaly detection (AD) when operating in non-stationary e…
Interference Detection and Exploitation for Multi-User Radar Sensing
Laurits Randers, Martin Voigt Vejling, Petar Popovski
Integrated sensing and communication is a key feature in next-generation wireless networks, enabling joint data transmission and environmental radar sensing on shared spectrum. In…
Conformal novelty detection for replicate point patterns with FDR or FWER control
Christophe A. N. Biscio, Adrien Mazoyer, Martin V. Vejling
Monte Carlo tests are widely used for computing valid p-values without requiring known distributions of test statistics. When performing multiple Monte Carlo tests, it is essential…
Conformal Data Contamination Tests for Trading or Sharing of Data
Martin V. Vejling, Shashi Raj Pandey, Christophe A. N. Biscio +1
The amount of quality data in many machine learning tasks is limited to what is available locally to data owners. The set of quality data can be expanded through trading or sharing…
Learning-Based Rich Feedback HARQ for Energy-Efficient Uplink Short Packet Transmission
Martin Voigt Vejling, Federico Chiariotti, Anders Ellersgaard Kalør +3
The trade-off between reliability, latency, and energy efficiency is a central problem in communication systems. Advanced hybrid automated repeat request (HARQ) techniques reduce r…