1 citations · 1 across the 6 of their papers we have counts for
6 papers
Scalable Multivariate Fronthaul Quantization for Cell-Free Massive MIMO
Sangwoo Park, Ahmet Hasim Gokceoglu, Li Wang +1
The conventional approach to the fronthaul design for cell-free massive MIMO system follows the compress-and-precode (CP) paradigm. Accordingly, encoded bits and precoding coeffici…
Generalization and Informativeness of Conformal Prediction
Matteo Zecchin, Sangwoo Park, Osvaldo Simeone +1
The safe integration of machine learning modules in decision-making processes hinges on their ability to quantify uncertainty. A popular technique to achieve this goal is conformal…
Cross-Validation Conformal Risk Control
Kfir M. Cohen, Sangwoo Park, Osvaldo Simeone +1
Conformal risk control (CRC) is a recently proposed technique that applies post-hoc to a conventional point predictor to provide calibration guarantees. Generalizing conformal pred…
Forking Uncertainties: Reliable Prediction and Model Predictive Control with Sequence Models via Conformal Risk Control
Matteo Zecchin, Sangwoo Park, Osvaldo Simeone
In many real-world problems, predictions are leveraged to monitor and control cyber-physical systems, demanding guarantees on the satisfaction of reliability and safety requirement…
Adaptive and Flexible Model-Based AI for Deep Receivers in Dynamic Channels
Tomer Raviv, Sangwoo Park, Osvaldo Simeone +2
Artificial intelligence (AI) is envisioned to play a key role in future wireless technologies, with deep neural networks (DNNs) enabling digital receivers to learn to operate in ch…
Robust Bayesian Learning for Reliable Wireless AI: Framework and Applications
Matteo Zecchin, Sangwoo Park, Osvaldo Simeone +2
This work takes a critical look at the application of conventional machine learning methods to wireless communication problems through the lens of reliability and robustness. Deep…