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cs.LG2025

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…

cs.LG2025

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…

eess.SP2025

xApp Conflict Mitigation with Scheduler

Idris Cinemre, Toktam Mahmoodi, Amirmohammad Farzaneh

Open RAN (O-RAN) fosters multi-vendor interoperability and data-driven control but simultaneously introduces the challenge of coordinating pre-trained xApps that may produce confli…

cs.LG2025

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…

cs.LG2025

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…