15 citations · 29 across the 41 of their papers we have counts for
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Conformal Sequential Decision Making With Cost and Sublinear Policy Regret Guarantees
Jayadev Naram, Giuseppe Durisi, Matteo Zecchin +1
Automated decision makers, such as AI agents that control robots or network devices, must often satisfy hard cost constraints while maintaining competitive performance. In such set…
Distributed Dynamic Associative Memory via Online Convex Optimization
Bowen Wang, Matteo Zecchin, Osvaldo Simeone
An associative memory (AM) enables cue-response recall, and it has recently been recognized as a key mechanism underlying modern neural architectures such as Transformers. In this…
Reliable Inference in Edge-Cloud Model Cascades via Conformal Alignment
Jiayi Huang, Sangwoo Park, Nicola Paoletti +1
Edge intelligence enables low-latency inference via compact on-device models, but assuring reliability remains challenging. We study edge-cloud cascades that must preserve conditio…
Distributed Associative Memory via Online Convex Optimization
Bowen Wang, Matteo Zecchin, Osvaldo Simeone
An associative memory (AM) enables cue-response recall, and associative memorization has recently been noted to underlie the operation of modern neural architectures such as Transf…
Optimizing In-Context Learning for Efficient Full Conformal Prediction
Weicao Deng, Sangwoo Park, Min Li +1
Reliable uncertainty quantification is critical for trustworthy AI. Conformal Prediction (CP) provides prediction sets with distribution-free coverage guarantees, but its two main…
Reliable Wireless Indoor Localization via Cross-Validated Prediction-Powered Calibration
Seonghoon Yoo, Houssem Sifaou, Sangwoo Park +2
Wireless indoor localization using predictive models with received signal strength information (RSSI) requires proper calibration for reliable position estimates. One remedy is to…
Mirror Online Conformal Prediction with Intermittent Feedback
Bowen Wang, Matteo Zecchin, Osvaldo Simeone
Online conformal prediction enables the runtime calibration of a pre-trained artificial intelligence model using feedback on its performance. Calibration is achieved through set pr…
Generalization and Informativeness of Weighted Conformal Risk Control Under Covariate Shift
Matteo Zecchin, Fredrik Hellström, Sangwoo Park +2
Predictive models are often required to produce reliable predictions under statistical conditions that are not matched to the training data. A common type of training-testing misma…
Distilling Calibration via Conformalized Credal Inference
Jiayi Huang, Sangwoo Park, Nicola Paoletti +1
Deploying artificial intelligence (AI) models on edge devices involves a delicate balance between meeting stringent complexity constraints, such as limited memory and energy resour…
Robust Bayesian Optimization via Localized Online Conformal Prediction
Dongwon Kim, Matteo Zecchin, Sangwoo Park +2
Bayesian optimization (BO) is a sequential approach for optimizing black-box objective functions using zeroth-order noisy observations. In BO, Gaussian processes (GPs) are employed…
Automatic AI Model Selection for Wireless Systems: Online Learning via Digital Twinning
Qiushuo Hou, Matteo Zecchin, Sangwoo Park +4
In modern wireless network architectures, such as O-RAN, artificial intelligence (AI)-based applications are deployed at intelligent controllers to carry out functionalities like s…
Calibrating Bayesian Learning via Regularization, Confidence Minimization, and Selective Inference
Jiayi Huang, Sangwoo Park, Osvaldo Simeone
The application of artificial intelligence (AI) models in fields such as engineering is limited by the known difficulty of quantifying the reliability of an AI's decision. A well-c…
Multi-Fidelity Bayesian Optimization With Across-Task Transferable Max-Value Entropy Search
Yunchuan Zhang, Sangwoo Park, Osvaldo Simeone
In many applications, ranging from logistics to engineering, a designer is faced with a sequence of optimization tasks for which the objectives are in the form of black-box functio…
Conservative and Risk-Aware Offline Multi-Agent Reinforcement Learning
Eslam Eldeeb, Houssem Sifaou, Osvaldo Simeone +2
Reinforcement learning (RL) has been widely adopted for controlling and optimizing complex engineering systems such as next-generation wireless networks. An important challenge in…
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…