b'Sangwoo Park'

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Featured Co-authors

Petar Popovski
170 publications
Osvaldo Simeone
158 publications
Yonina C. Eldar
157 publications
Nir Shlezinger
69 publications
Shlomo Shamai
66 publications
David Gesbert
50 publications
Marios Kountouris
34 publications
Matei Ciocarlie
32 publications
Moongu Jeon
30 publications
Hyeryung Jang
22 publications
Caili Guo
22 publications

research

∙ 08/08/2023

Federated Inference with Reliable Uncertainty Quantification over Wireless Channels via Conformal Prediction

Consider a setting in which devices and a server share a pre-trained mod...

0 Meiyi Zhu, et al. ∙

research

∙ 06/30/2023

Bayesian Optimization with Formal Safety Guarantees via Online Conformal Prediction

Black-box zero-th order optimization is a central primitive for applicat...

0 Yunchuan Zhang, et al. ∙

research

∙ 05/18/2023

SpikeCP: Delay-Adaptive Reliable Spiking Neural Networks via Conformal Prediction

Spiking neural networks (SNNs) process time-series data via internal eve...

0 Jiechen Chen, et al. ∙

research

∙ 05/12/2023

Calibration-Aware Bayesian Learning

Deep learning models, including modern systems like large language model...

0 Jiayi Huang, et al. ∙

research

∙ 05/12/2023

Adaptive and Flexible Model-Based AI for Deep Receivers in Dynamic Channels

Artificial intelligence (AI) is envisioned to play a key role in future ...

0 Tomer Raviv, et al. ∙

research

∙ 04/06/2023

Quantum Conformal Prediction for Reliable Uncertainty Quantification in Quantum Machine Learning

Quantum machine learning is a promising programming paradigm for the opt...

0 Sangwoo Park, et al. ∙

research

∙ 02/15/2023

Guaranteed Dynamic Scheduling of Ultra-Reliable Low-Latency Traffic via Conformal Prediction

The dynamic scheduling of ultra-reliable and low-latency traffic (URLLC)...

0 Kfir M. Cohen, et al. ∙

research

∙ 02/05/2023

Modular Model-Based Bayesian Learning for Uncertainty-Aware and Reliable Deep MIMO Receivers

In the design of wireless receivers, DNNs can be combined with tradition...

0 Tomer Raviv, et al. ∙

research

∙ 12/15/2022

Calibrating AI Models for Wireless Communications via Conformal Prediction

When used in complex engineered systems, such as communication networks,...

0 Kfir M. Cohen, et al. ∙

research

∙ 10/29/2022

Fast-Convergent Federated Learning via Cyclic Aggregation

Federated learning (FL) aims at optimizing a shared global model over mu...

0 Youngjoon Lee, et al. ∙

research

∙ 10/29/2022

Security-Preserving Federated Learning via Byzantine-Sensitive Triplet Distance

While being an effective framework of learning a shared model across mul...

0 Youngjoon Lee, et al. ∙

research

∙ 10/10/2022

Calibrating AI Models for Few-Shot Demodulation via Conformal Prediction

AI tools can be useful to address model deficits in the design of commun...

0 Kfir M. Cohen, et al. ∙

research

∙ 10/06/2022

Few-Shot Calibration of Set Predictors via Meta-Learned Cross-Validation-Based Conformal Prediction

Conventional frequentist learning is known to yield poorly calibrated mo...

0 Sangwoo Park, et al. ∙

research

∙ 07/13/2022

Continual Meta-Reinforcement Learning for UAV-Aided Vehicular Wireless Networks

Unmanned aerial base stations (UABSs) can be deployed in vehicular wirel...

0 Riccardo Marini, et al. ∙

research

∙ 07/01/2022

Robust Bayesian Learning for Reliable Wireless AI: Framework and Applications

This work takes a critical look at the application of conventional machi...

0 Matteo Zecchin, et al. ∙

research

∙ 03/27/2022

Online Meta-Learning For Hybrid Model-Based Deep Receivers

Recent years have witnessed growing interest in the application of deep ...

0 Tomer Raviv, et al. ∙

research

∙ 03/23/2022

Predicting Multi-Antenna Frequency-Selective Channels via Meta-Learned Linear Filters based on Long-Short Term Channel Decomposition

An efficient data-driven prediction strategy for multi-antenna frequency...

0 Sangwoo Park, et al. ∙

research

∙ 03/03/2022

Robust PAC^m: Training Ensemble Models Under Model Misspecification and Outliers

Standard Bayesian learning is known to have suboptimal generalization ca...

0 Matteo Zecchin, et al. ∙

research

∙ 10/05/2021

Design of Spiral-Cable Forearm Exoskeleton to Provide Supination Adjustment for Hemiparetic Stroke Subjects

We present the development of a cable-based passive forearm exoskeleton,...

0 Ava Chen, et al. ∙

research

∙ 10/05/2021

Thumb Assistance Via Active and Passive Exotendons in a Robotic Hand Orthosis for Stroke

We present a tendon-driven, active-extension thumb exoskeleton adding op...

0 Ava Chen, et al. ∙

research

∙ 10/01/2021

Predicting Flat-Fading Channels via Meta-Learned Closed-Form Linear Filters and Equilibrium Propagation

Predicting fading channels is a classical problem with a vast array of a...

0 Sangwoo Park, et al. ∙

research

∙ 08/02/2021

Learning to Learn to Demodulate with Uncertainty Quantification via Bayesian Meta-Learning

Meta-learning, or learning to learn, offers a principled framework for f...

0 Kfir M. Cohen, et al. ∙

research

∙ 06/01/2021

Information-Theoretic Analysis of Epistemic Uncertainty in Bayesian Meta-learning

The overall predictive uncertainty of a trained predictor can be decompo...

0 Sharu Theresa Jose, et al. ∙

research

∙ 03/24/2021

Meta-ViterbiNet: Online Meta-Learned Viterbi Equalization for Non-Stationary Channels

Deep neural networks (DNNs) based digital receivers can potentially oper...

0 Tomer Raviv, et al. ∙

research

∙ 12/26/2020

Balance-Oriented Focal Loss with Linear Scheduling for Anchor Free Object Detection

Most existing object detectors suffer from class imbalance problems that...

0 Hopyong Gil, et al. ∙

research

∙ 10/30/2020

Semi-Supervised Intent Inferral Using Ipsilateral Biosignals on a Hand Orthosis for Stroke Subjects

In order to provide therapy in a functional context, controls for wearab...

0 Cassie Meeker, et al. ∙

research

∙ 03/03/2020

End-to-End Fast Training of Communication Links Without a Channel Model via Online Meta-Learning

When a channel model is not available, the end-to-end training of encode...

0 Sangwoo Park, et al. ∙

research

∙ 01/05/2020

From Learning to Meta-Learning: Reduced Training Overhead and Complexity for Communication Systems

Machine learning methods adapt the parameters of a model, constrained to...

0 Osvaldo Simeone, et al. ∙

research

∙ 11/18/2019

User-Driven Functional Movement Training with a Wearable Hand Robot after Stroke

We studied the performance of a robotic orthosis designed to assist the ...

0 Sangwoo Park, et al. ∙

research

∙ 10/22/2019

Meta-Learning to Communicate: Fast End-to-End Training for Fading Channels

When a channel model is available, learning how to communicate on fading...

0 Sangwoo Park, et al. ∙

research

∙ 10/22/2019

Drivers Drowsiness Detection using Condition-Adaptive Representation Learning Framework

We propose a condition-adaptive representation learning framework for th...

21 Jongmin Yu, et al. ∙

research

∙ 08/23/2019

Learning to Demodulate from Few Pilots via Offline and Online Meta-Learning

This paper considers an Internet-of-Things (IoT) scenario in which devic...

0 Sangwoo Park, et al. ∙

research

∙ 03/06/2019

Learning How to Demodulate from Few Pilots via Meta-Learning

Consider an Internet-of-Things (IoT) scenario in which devices transmit ...

0 Sangwoo Park, et al. ∙

research

∙ 07/31/2018

Multimodal Sensing and Interaction for a Robotic Hand Orthosis

Wearable robotic hand rehabilitation devices can allow greater freedom a...

0 Sangwoo Park, et al. ∙

research

∙ 02/16/2018

Design and Development of Effective Transmission Mechanisms on a Tendon Driven Hand Orthosis for Stroke Patients

Tendon-driven hand orthoses have advantages over exoskeletons with respe...

0 Sangwoo Park, et al. ∙

research

∙ 02/01/2018

EMG Pattern Classification to Control a Hand Orthosis for Functional Grasp Assistance after Stroke

Wearable orthoses can function both as assistive devices, which allow th...

0 Cassie Meeker, et al. ∙

research

∙ 12/19/2017

On the Feasibility of Wearable Exotendon Networks for Whole-Hand Movement Patterns in Stroke Patients

Fully wearable hand rehabilitation and assistive devices could extend tr...

0 Sangwoo Park, et al. ∙

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