.- 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.

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