14 citations · 16 across the 16 of their papers we have counts for
20 papers
FedSwitch: Federated Region Classification From Wireless Channel Measurements
Mattia Piana, Stefano Rini, Stefano Tomasin
Wireless Internet-of-Things (IoT) networks can leverage locally observed channel state information (CSI) at base-stations (BSs) to perform region classification, i.e., infer the re…
The Path Matters: Evaluating Small Language Models Beyond Answer Accuracy in KGQA
Eduin E. Hernandez, Sergio A. Diaz, Luis F. Garcia +2
Small language models (SLMs) are increasingly paired with knowledge graphs (KGs), yet end-to-end KG question answering conflates graph access, search, navigation, reasoning, and an…
Theseus in the Graph: Towards Traceable Multi-Hop Graph Navigation
Eduin E. Hernandez, Luis F. Garcia, Nurassyl Askar +2
Multi-Hop Knowledge Graph Question Answering (KGQA) tasks require models to assemble relational evidence along paths in a KG to answer natural-language questions. However, existing…
NARRAS: Edge-Triggered Distributed Inference for CSI-Based Localization in Vehicular IoT Networks
Rodrigo Oliver, Ricardo Vazquez Alvarez, Alejandro Lancho +1
CSI-based localization with spatially distributed antenna arrays exposes a basic resource trade-off. Each array can provide a rich view of the channel, but forwarding observations…
JGRA: Jacobian Geometry Robustness Assessment in NISQ Noise-Aware Quantum Neural Networks
Gianluca Scanu, Luca Barletta, Stefano Rini
The NISQ era places stringent constraints on quantum computation, where noise and decoherence fundamentally limit performance. In classical deep learning, model robustness and resi…
PolarZero: A Reinforcement Learning Approach for Low-Complexity Polarization Kernel Design
Yi-Ting Hong, Stefano Rini, Luca Barletta
Polar codes with large kernels can achieve improved error exponents but are challenging to design with low decoding complexity. This work investigates kernel construction under rec…
STSM-FiLM: A FiLM-Conditioned Neural Architecture for Time-Scale Modification of Speech
Dyah A. M. G. Wisnu, Ryandhimas E. Zezario, Stefano Rini +4
Time-Scale Modification (TSM) of speech aims to alter the playback rate of audio without changing its pitch. While classical methods like Waveform Similarity-based Overlap-Add (WSO…
Improving Perceptual Audio Aesthetic Assessment via Triplet Loss and Self-Supervised Embeddings
Dyah A. M. G. Wisnu, Ryandhimas E. Zezario, Stefano Rini +2
We present a system for automatic multi-axis perceptual quality prediction of generative audio, developed for Track 2 of the AudioMOS Challenge 2025. The task is to predict four Au…
DOA Estimation via Optimal Weighted Low-Rank Matrix Completion
Saeed Razavikia, Mohammad Bokaei, Arash Amini +2
This paper presents a novel method for estimating the direction of arrival (DOA) for a non-uniform and sparse linear sensor array using the weighted lifted structure low-rank matri…
PNCS:Power-Norm Cosine Similarity for Diverse Client Selection in Federated Learning
Liangyan Li, Yangyi Liu, Yimo Ning +2
Federated Learning (FL) has emerged as a powerful paradigm for leveraging diverse datasets from multiple sources while preserving data privacy by avoiding centralized storage. Howe…
Reinforcement Learning-Aided Design of Efficient Polarization Kernels
Yi-Ting Hong, Stefano Rini, Luca Barletta
Polar codes with large kernels achieve optimal error exponents but are difficult to construct when low decoding complexity is also required. We address this challenge under recursi…
PAUSE: Low-Latency and Privacy-Aware Active User Selection for Federated Learning
Ori Peleg, Natalie Lang, Dan Ben Ami +3
Federated learning (FL) enables multiple edge devices to collaboratively train a machine learning model without the need to share potentially private data. Federated learning proce…
The Query/Hit Model for Sequential Hypothesis Testing
Mahshad Shariatnasab, Stefano Rini, Farhad Shirani +1
This work introduces the Query/Hit (Q/H) learning model. The setup consists of two agents. One agent, Alice, has access to a streaming source, while the other, Bob, does not have d…
Age-of-Gradient Updates for Federated Learning over Random Access Channels
Yu Heng Wu, Houman Asgari, Stefano Rini +1
This paper studies the problem of federated training of a deep neural network (DNN) over a random access channel (RACH) such as in computer networks, wireless networks, and cellula…
ARMA Processes with Discrete-Continuous Excitation: Compressibility Beyond Sparsity
Mohammad-Amin Charusaie, Stefano Rini, Arash Amini
Rényi Information Dimension (RID) plays a central role in quantifying the compressibility of random variables with singularities in their distribution, encompassing and extending b…
Coding for the unsourced B-channel with erasures: enhancing the linked loop code
William W. Zheng, Jamison R. Ebert, Stefano Rini +1
In [1], the linked loop code (LLC) is presented as a promising code for the unsourced A-channel with erasures (UACE). The UACE is an unsourced multiple access channel in which acti…
HAAQI-Net: A Non-intrusive Neural Music Audio Quality Assessment Model for Hearing Aids
Dyah A. M. G. Wisnu, Stefano Rini, Ryandhimas E. Zezario +2
This paper introduces HAAQI-Net, a non-intrusive deep learning-based music audio quality assessment model for hearing aid users. Unlike traditional methods like the Hearing Aid Aud…
Coding for the unsourced A-channel with erasures: the linked loop code
William W. Zheng, Jamison R. Ebert, Stefano Rini +1
The A-channel is a noiseless multiple access channel in which users simultaneously transmit Q-ary symbols and the receiver observes the set of transmitted symbols, but not their mu…
Harmonic Retrieval Using Weighted Lifted-Structure Low-Rank Matrix Completion
Mohammad Bokaei, Saeed Razavikia, Stefano Rini +2
In this paper, we investigate the problem of recovering the frequency components of a mixture of complex sinusoids from a random subset of equally-spaced time-domain sample…
Empirical Risk Minimization with Relative Entropy Regularization
Samir M. Perlaza, Gaetan Bisson, Iñaki Esnaola +2
The empirical risk minimization (ERM) problem with relative entropy regularization (ERM-RER) is investigated under the assumption that the reference measure is a -finite measure…