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Multi-Fidelity Hybrid Reinforcement Learning via Information Gain Maximization
Houssem Sifaou, Osvaldo Simeone
Optimizing a reinforcement learning (RL) policy typically requires extensive interactions with a high-fidelity simulator of the environment, which are often costly or impractical.…
Synthetic Counterfactual Labels for Efficient Conformal Counterfactual Inference
Amirmohammad Farzaneh, Matteo Zecchin, Osvaldo Simeone
This work addresses the problem of constructing reliable prediction intervals for individual counterfactual outcomes. Existing conformal counterfactual inference (CCI) methods prov…
Online Conformal Anomaly Detection with Prediction-Powered Data Acquisition
Amirmohammad Farzaneh, Osvaldo Simeone
Online anomaly detection is essential in fields such as cybersecurity, healthcare, industrial monitoring, and telecommunications, where promptly identifying deviations from expecte…
SCAN-BEST: Sub-6GHz-Aided Near-field Beam Selection with Formal Reliability Guarantees
Weicao Deng, Binpu Shi, Min Li +1
As millimeter-wave (mmWave) MIMO systems adopt larger antenna arrays, near-field propagation becomes increasingly prominent, especially for users close to the transmitter. Traditio…
Ensuring Reliability via Hyperparameter Selection: Review and Advances
Amirmohammad Farzaneh, Osvaldo Simeone
Hyperparameter selection is a critical step in the deployment of artificial intelligence (AI) models, particularly in the current era of foundational, pre-trained, models. By frami…
Multi-Objective Hyperparameter Selection via Hypothesis Testing on Reliability Graphs
Amirmohammad Farzaneh, Osvaldo Simeone
The selection of hyperparameters, such as prompt templates in large language models (LLMs), must often strike a balance between reliability and cost. In many cases, structural rela…