An Efficient Multi-Link Channel Model for LiFi
The emergence of LiFi for indoor communications opens up new possibilities for wireless services in crowded multiuser scenarios. The deployment of LiFi in indoor scenarios is challenging due to the line-of-sight (LOS) blockage as well as...
Clustered Federated Learning: Model-Agnostic Distributed Multi-Task Optimization under Privacy Constraints
Federated learning (FL) is the most widely adopted framework for collaborative training of deep learning models under privacy constraints. Albeit its popularity, it has been observed that FL yields suboptimal results if the clients’ data...
Zero on Shape: A Generic 2D-3D Instance Similarity Metric learned from Synthetic Data
We present a network architecture which compares RGB images and untextured 3D models by the similarity of the represented shape. Our system is optimised for Zero-Shot retrieval, meaning it can recognise shapes never shown in training.
Enabling S-C-L-Band Systems with Standard C-Band Modulator and Coherent Receiver using Nonlinear Predistortion
To counteract the forthcoming capacity crunch in optical networks by increasing the throughput over already existing fiber infrastructures, innovative approaches are required. Multiband systems are an interesting approach to address this issue....
S-Band Transmission with Off-the-Shelf C-Band Components Enabled by Nonlinear Predistortion based on Coherent System Identification
Nonlinear Predistortion based on Coherent System Identification Text: In order to cope with the rapid traffic growth and as well reducing the cost-per-bit, reuse of the legacy optical fiber infrastructure is one of the main objectives for...
FantastIC4: A Hardware-Software Co-Design Approach for Efficiently Running 4bit-Compact Multilayer Perceptrons
With the growing demand for deploying Deep Learning models to the “edge”, it is paramount to develop techniques that allow to execute models within very tight and limited resource constraints. In this work we propose a software-hardware...
Explain and Improve: LRP-Inference Fine Tuning for Image Captioning Models
This paper analyzes the predictions of image captioning models with attention mechanisms beyond visualizing the attention itself. We compare the interpretability of attention heatmaps systematically against the explanations. We demonstrate that...
Inter-Operator Machine Learning Model Trading over Acumos AI Federated Marketplace
We demonstrate the development of a QoT classifier over an autonomous machine-learning pipeline, the trading of the classifier over a federated marketplace, and eventually its deployment in the customer’s network as a cloud-native...
Deep Convolutional Neural Network for Network-wide QoT Estimation
We propose a novel Deep Convolutional Neural Network formulation for network-wide QoT classification tasks and show its effectiveness for networks with significant topological differences. Our formulation achieves ~99% accuracy on large and...
Benefits of MIMO Mode Switching, Angular Diversity and Multiuser Multiplexing for LiFi
We report on the first real-time experiments with distributed MIMO and multiple users for LiFi. MIMO mode switching and angular diversity are beneficial for robust-ness. Multiuser multiplexing helps in scenarios where users have complementary...