119 citations · 172 across the 15 of their papers we have counts for
20 papers
TerMeZO: Ternary Sparse Zeroth-Order Optimization for Fine-tuning BitNet Models at the Edge
Houssem Sifaou, Prabodh Katti, Bipin Rajendran +1
Fine-tuning anguage models (LLMs) with first-order optimizers requires a memory several times larger than that required for inference. Memory-efficient zeroth-order optimization (M…
Event-triggered Implicit Perturbation for Zeroth-Order Fine-Tuning of Spiking Transformers
Tengteng Lei, Prabodh Katti, Rashi Dutt +5
Zeroth-order (ZO) optimization estimates gradients using only forward-pass evaluations, making it suitable for fine-tuning non-differentiable, event-driven spiking neural networks…
Asymptotic Behavior of Multi--Task Learning: Implicit Regularization and Double Descent Effects
Ayed M. Alrashdi, Oussama Dhifallah, Houssem Sifaou
Multi--task learning seeks to improve the generalization error by leveraging the common information shared by multiple related tasks. One challenge in multi--task learning is ident…
Multi-Fidelity Hybrid Reinforcement Learning via Information Gain Maximization
Houssem Sifaou, Osvaldo Simeone
Optimizing a reinforcement learning (RL) policy typically requires extensive interactions with a high-fidelity simulator of the environment, which are often costly or impractical.…
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…
How to Bridge the Sim-to-Real Gap in Digital Twin-Aided Telecommunication Networks
Clement Ruah, Houssem Sifaou, Osvaldo Simeone +1
Training effective artificial intelligence models for telecommunications is challenging due to the scarcity of deployment-specific data. Real data collection is expensive, and avai…
Context-Aware Doubly-Robust Semi-Supervised Learning
Clement Ruah, Houssem Sifaou, Osvaldo Simeone +1
The widespread adoption of artificial intelligence (AI) in next-generation communication systems is challenged by the heterogeneity of traffic and network conditions, which call fo…
Semi-Supervised Learning via Cross-Prediction-Powered Inference for Wireless Systems
Houssem Sifaou, Osvaldo Simeone
In many wireless application scenarios, acquiring labeled data can be prohibitively costly, requiring complex optimization processes or measurement campaigns. Semi-supervised learn…
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…
Over-The-Air Federated Learning Over Scalable Cell-free Massive MIMO
Houssem Sifaou, Geoffrey Ye Li
Cell-free massive MIMO is emerging as a promising technology for future wireless communication systems, which is expected to offer uniform coverage and high spectral efficiency com…
Over-The-Air Federated Learning under Byzantine Attacks
Houssem Sifaou, Geoffrey Ye Li
Federated learning (FL) is a promising solution to enable many AI applications, where sensitive datasets from distributed clients are needed for collaboratively training a global m…
CSI-fingerprinting Indoor Localization via Attention-Augmented Residual Convolutional Neural Network
Bowen Zhang, Houssem Sifaou, Geoffrey Ye Li
Deep learning has been widely adopted for channel state information (CSI)-fingerprinting indoor localization systems. These systems usually consist of two main parts, i.e., a posit…
Robust Federated Learning via Over-The-Air Computation
Houssem Sifaou, Geoffrey Ye Li
This paper investigates the robustness of over-the-air federated learning to Byzantine attacks. The simple averaging of the model updates via over-the-air computation makes the lea…
Performance Analysis of Regularized Convex Relaxation for Complex-Valued Data Detection
Ayed M. Alrashdi, Houssem Sifaou
In this work, we study complex-valued data detection performance in massive multiple-input multiple-output (MIMO) systems. We focus on the problem of recovering an -dimensional…
A Precise Performance Analysis of Support Vector Regression
Houssem Sifaou, Abla kammoun, Mohamed-Slim Alouini
In this paper, we study the hard and soft support vector regression techniques applied to a set of linear measurements of the form wh…
Precise Error Analysis of the LASSO under Correlated Designs
Ayed M. Alrashdi, Houssem Sifaou, Abla Kammoun +2
In this paper, we consider the problem of recovering a sparse signal from noisy linear measurements using the so called LASSO formulation. We assume a correlated Gaussian design ma…
High-Dimensional Quadratic Discriminant Analysis under Spiked Covariance Model
Houssem Sifaou, Abla Kammoun, Mohamed-Slim Alouini
Quadratic discriminant analysis (QDA) is a widely used classification technique that generalizes the linear discriminant analysis (LDA) classifier to the case of distinct covarianc…
Optimal Linear Precoding for Indoor Visible Light Communication System
Houssem Sifaou, Ki-Hong Park, Abla Kammoun +1
Visible light communication (VLC) is an emerging technique that uses light-emitting diodes (LED) to combine communication and illumination. It is considered as a promising scheme f…
Precoding design for single-RF massive MIMO systems: A large system analysis
Houssem Sifaou, Abla Kammoun, Mohamed-Slim Alouini
This work revisits a recently proposed precoding design for massive multiple-input multiple output (MIMO) systems that is based on the use of an instantaneous total power constrain…
Max-Min SINR in Large-Scale Single-Cell MU-MIMO: Asymptotic Analysis and Low Complexity Transceivers
Houssem Sifaou, Abla Kammoun, Luca Sanguinetti +2
This work focuses on the downlink and uplink of large-scale single-cell MU-MIMO systems in which the base station (BS) endowed with antennas communicates with single-antenn…