28 citations · 61 across the 15 of their papers we have counts for
17 papers
TransCoder: A Neural-Enhancement Framework for Channel Codes
Anastasiia Kurmukova, Selim F. Yilmaz, Emre Ozfatura +1
Reliable communication over noisy channels requires the design of specialized error-correcting codes (ECCs) tailored to specific system requirements. Recently, neural network-based…
Learning to Interfere in Non-Orthogonal Multiple-Access Joint Source-Channel Coding
Selim F. Yilmaz, Can Karamanli, Deniz Gunduz
We consider multiple transmitters aiming to communicate their source signals (e.g., images) over a multiple access channel (MAC). Conventional communication systems minimize interf…
SING: Semantic Image Communications using Null-Space and INN-Guided Diffusion Models
Jiakang Chen, Selim F. Yilmaz, Di You +2
Joint source-channel coding systems based on deep neural networks (DeepJSCC) have recently demonstrated remarkable performance in wireless image transmission. Existing methods prim…
Federated Learning in Mobile Networks: A Comprehensive Case Study on Traffic Forecasting
Nikolaos Pavlidis, Vasileios Perifanis, Selim F. Yilmaz +6
The increasing demand for efficient resource allocation in mobile networks has catalyzed the exploration of innovative solutions that could enhance the task of real-time cellular t…
Private Collaborative Edge Inference via Over-the-Air Computation
Selim F. Yilmaz, Burak Hasircioglu, Li Qiao +1
We consider collaborative inference at the wireless edge, where each client's model is trained independently on its local dataset. Clients are queried in parallel to make an accura…
Distributed Deep Joint Source-Channel Coding with Decoder-Only Side Information
Selim F. Yilmaz, Ezgi Ozyilkan, Deniz Gunduz +1
We consider low-latency image transmission over a noisy wireless channel when correlated side information is present only at the receiver side (the Wyner-Ziv scenario). In particul…
Towards Energy-Aware Federated Traffic Prediction for Cellular Networks
Vasileios Perifanis, Nikolaos Pavlidis, Selim F. Yilmaz +6
Cellular traffic prediction is a crucial activity for optimizing networks in fifth-generation (5G) networks and beyond, as accurate forecasting is essential for intelligent network…
High Perceptual Quality Wireless Image Delivery with Denoising Diffusion Models
Selim F. Yilmaz, Xueyan Niu, Bo Bai +3
We consider the image transmission problem over a noisy wireless channel via deep learning-based joint source-channel coding (DeepJSCC) along with a denoising diffusion probabilist…
Distributed Deep Joint Source-Channel Coding over a Multiple Access Channel
Selim F. Yilmaz, Can Karamanli, Deniz Gunduz
We consider distributed image transmission over a noisy multiple access channel (MAC) using deep joint source-channel coding (DeepJSCC). It is known that Shannon's separation theor…
Federated Spatial Reuse Optimization in Next-Generation Decentralized IEEE 802.11 WLANs
Francesc Wilhelmi, Jernej Hribar, Selim F. Yilmaz +10
As wireless standards evolve, more complex functionalities are introduced to address the increasing requirements in terms of throughput, latency, security, and efficiency. To unlea…
Over-the-Air Ensemble Inference with Model Privacy
Selim F. Yilmaz, Burak Hasircioglu, Deniz Gunduz
We consider distributed inference at the wireless edge, where multiple clients with an ensemble of models, each trained independently on a local dataset, are queried in parallel to…
PySAD: A Streaming Anomaly Detection Framework in Python
Selim F. Yilmaz, Suleyman S. Kozat
Streaming anomaly detection requires algorithms that operate under strict constraints: bounded memory, single-pass processing, and constant-time complexity. We present PySAD, a com…
Multi-Label Sentiment Analysis on 100 Languages with Dynamic Weighting for Label Imbalance
Selim F. Yilmaz, E. Batuhan Kaynak, Aykut Koç +2
We investigate cross-lingual sentiment analysis, which has attracted significant attention due to its applications in various areas including market research, politics and social s…
Unsupervised Anomaly Detection via Deep Metric Learning with End-to-End Optimization
Selim F. Yilmaz, Suleyman S. Kozat
We investigate unsupervised anomaly detection for high-dimensional data and introduce a deep metric learning (DML) based framework. In particular, we learn a distance metric throug…
Achieving Online Regression Performance of LSTMs with Simple RNNs
N. Mert Vural, Fatih Ilhan, Selim F. Yilmaz +2
Recurrent Neural Networks (RNNs) are widely used for online regression due to their ability to generalize nonlinear temporal dependencies. As an RNN model, Long-Short-Term-Memory N…
RNN-based Online Learning: An Efficient First-Order Optimization Algorithm with a Convergence Guarantee
N. Mert Vural, Selim F. Yilmaz, Fatih Ilhan +1
We investigate online nonlinear regression with continually running recurrent neural network networks (RNNs), i.e., RNN-based online learning. For RNN-based online learning, we int…
Deception Detection by 2D-to-3D Face Reconstruction from Videos
Minh Ngô, Burak Mandira, Selim Fırat Yılmaz +5
Lies and deception are common phenomena in society, both in our private and professional lives. However, humans are notoriously bad at accurate deception detection. Based on the li…