Machine Learning and Principles and Practice of Knowledge Discovery in Databases

.- Challenges and Opportunities of Large Language Models in Real-World Machine Learning Applications.

.- Contextual Data Augmentation for Task-Oriented Dialog Systems.

.- Fairness of ChatGPT and the Role Of Explainable-Guided Prompts.

.- Deep learning meets Neuromorphic Hardware.

.- Non-Dissipative Propagation by Randomized Anti-Symmetric Deep Graph Networks.

.- On the Noise Robustness of Analog Complex-Valued Neural Networks.

.- Neu-BrAuER: a neuromorphic Braille letters audio-reader for commercial edge devices.

.- Discovery challenge.

.- Transductive Fire-affected Area Segmentation with False-Color Data.

.- Post Wildfire Burnt-up Detection using Siamese UNet.

.- Predicting Exoplanetary Features with a Residual Model for Uniform and Gaussian Distributions.

.- Reproducing Bayesian Posterior Distributions for Exoplanet Atmospheric Parameter Retrievals with a Machine Learning Surrogate Model.

.- Simulation-based Inference for Exoplanet Atmospheric Retrieval: Insights from winning the Ariel Data Challenge 2023 using Normalizing Flows.

.- ITEM: IoT, Edge, and Mobile for Embedded Machine Learning.

.- Implications of Noise in Resistive Memory on Deep Neural Networks for Image Classification.

.- Evaluating custom-precision operator support in MLIR for ARM CPUs.

.- microYOLO: Towards Single-Shot Object Detection on Microcontrollers.

.- OptiSim: A Hardware-Aware Optimization Space Exploration Tool for CNN Architectures.

.- On the Non-Associativity of Analog Computations.

.- Quantized dynamics models for hardware-efficient control and planning in model-based RL.

.- LIMBO - LearnIng and Mining for BlOckchains.

.- Temporal and Geographical Analysis of Real Economic Activities in the Bitcoin Blockchain.

.- Machine Learning for Cybersecurity (MLCS 2023).

.- A source separation approach to temporal graph modelling for computer networks.

.- Quantum Machine Learning for Malware Classification.

.- Side-channel Based Intrusion Detection for Network Equipment.

.- I See Dead People: Gray-Box Adversarial Attack on Image-To-Text Models.

.- Concept Drift Detection using Ensemble of Integrally Private Models.

.- MIDAS - The 8th Workshop on MIning DAta for financial applicationS.

.- ViBERTgrid BiLSTM-CRF: Multimodal Key Information Extraction from Unstructured Financial Documents.

.- Comparing Deep RL and Traditional Financial Portfolio Methods  - Full paper.

.- Occupational Fraud Detection through Agent-based Data Generation.

.- Stock Price Time Series Forecasting Using Dynamic Graph Neural Networks and Attention Mechanism in Recurrent Neural Networks.

.- Flexible Tails for Normalising Flows, with Application to the Modelling of Financial Return Data.

.- Exploring Alternative Data for Nowcasting: A Case Study on US GDP using Topic Attention.

.- Topology-Agnostic Detection of Temporal Money Laundering Flows in Billion-Scale Transactions.

.- Boosting Credit Risk Data Quality using Machine Learning and eXplainable AI Techniques.

.- Ensemble methods for Stock Market Prediction.

.- Workshop on Advancements in Federated Learning.

.- Federated Learning with Neural Graphical Models.

.- On improving accuracy in Federated Learning using GANs-based pre-training and Ensemble Learning.

.- Re-evaluating the Privacy Benefit of Federated Learning.

.- Parameterizing Federated Continual Learning for Reproducible Research.