{"product_id":"machine-learning-and-principles-and-practice-of-knowledge-discovery-in-databases-9783031746420","title":"Machine Learning and Principles and Practice of Knowledge Discovery in Databases","description":"\u003cb\u003eBook Synopsis\u003c\/b\u003e\u003cbr\u003e\u003cp\u003e\u003cstrong\u003e.- Challenges and Opportunities of Large Language Models in Real-World Machine Learning Applications.\u003c\/strong\u003e\u003c\/p\u003e\u003cp\u003e.- Contextual Data Augmentation for Task-Oriented Dialog Systems.\u003c\/p\u003e\u003cp\u003e.- Fairness of ChatGPT and the Role Of Explainable-Guided Prompts.\u003c\/p\u003e\u003cp\u003e\u003cstrong\u003e.- Deep learning meets Neuromorphic Hardware.\u003c\/strong\u003e\u003c\/p\u003e\u003cp\u003e.- Non-Dissipative Propagation by Randomized Anti-Symmetric Deep Graph Networks.\u003c\/p\u003e\u003cp\u003e.- On the Noise Robustness of Analog Complex-Valued Neural Networks.\u003c\/p\u003e\u003cp\u003e.- Neu-BrAuER: a neuromorphic Braille letters audio-reader for commercial edge devices.\u003c\/p\u003e\u003cp\u003e\u003cstrong\u003e.- Discovery challenge.\u003c\/strong\u003e\u003c\/p\u003e\u003cp\u003e.- Transductive Fire-affected Area Segmentation with False-Color Data.\u003c\/p\u003e\u003cp\u003e.- Post Wildfire Burnt-up Detection using Siamese UNet.\u003c\/p\u003e\u003cp\u003e.- Predicting Exoplanetary Features with a Residual Model for Uniform and Gaussian Distributions.\u003c\/p\u003e\u003cp\u003e.- Reproducing Bayesian Posterior Distributions for Exoplanet Atmospheric Parameter Retrievals with a Machine Learning Surrogate Model.\u003c\/p\u003e\u003cp\u003e.- Simulation-based Inference for Exoplanet Atmospheric Retrieval: Insights from winning the Ariel Data Challenge 2023 using Normalizing Flows.\u003c\/p\u003e\u003cp\u003e\u003cstrong\u003e.- ITEM: IoT, Edge, and Mobile for Embedded Machine Learning.\u003c\/strong\u003e\u003c\/p\u003e\u003cp\u003e.- Implications of Noise in Resistive Memory on Deep Neural Networks for Image Classification.\u003c\/p\u003e\u003cp\u003e.- Evaluating custom-precision operator support in MLIR for ARM CPUs.\u003c\/p\u003e\u003cp\u003e.- microYOLO: Towards Single-Shot Object Detection on Microcontrollers.\u003c\/p\u003e\u003cp\u003e.- OptiSim: A Hardware-Aware Optimization Space Exploration Tool for CNN Architectures.\u003c\/p\u003e\u003cp\u003e.- On the Non-Associativity of Analog Computations.\u003c\/p\u003e\u003cp\u003e.- Quantized dynamics models for hardware-efficient control and planning in model-based RL.\u003c\/p\u003e\u003cp\u003e\u003cstrong\u003e.- LIMBO - LearnIng and Mining for BlOckchains.\u003c\/strong\u003e\u003c\/p\u003e\u003cp\u003e.- Temporal and Geographical Analysis of Real Economic Activities in the Bitcoin Blockchain.\u003c\/p\u003e\u003cp\u003e\u003cstrong\u003e.- Machine Learning for Cybersecurity (MLCS 2023).\u003c\/strong\u003e\u003c\/p\u003e\u003cp\u003e.- A source separation approach to temporal graph modelling for computer networks.\u003c\/p\u003e\u003cp\u003e.- Quantum Machine Learning for Malware Classification.\u003c\/p\u003e\u003cp\u003e.- Side-channel Based Intrusion Detection for Network Equipment.\u003c\/p\u003e\u003cp\u003e.- I See Dead People: Gray-Box Adversarial Attack on Image-To-Text Models.\u003c\/p\u003e\u003cp\u003e.- Concept Drift Detection using Ensemble of Integrally Private Models.\u003c\/p\u003e\u003cp\u003e\u003cstrong\u003e.- MIDAS - The 8th Workshop on MIning DAta for financial applicationS.\u003c\/strong\u003e\u003c\/p\u003e\u003cp\u003e.- ViBERTgrid BiLSTM-CRF: Multimodal Key Information Extraction from Unstructured Financial Documents.\u003c\/p\u003e\u003cp\u003e.- Comparing Deep RL and Traditional Financial Portfolio Methods  - Full paper.\u003c\/p\u003e\u003cp\u003e.- Occupational Fraud Detection through Agent-based Data Generation.\u003c\/p\u003e\u003cp\u003e.- Stock Price Time Series Forecasting Using Dynamic Graph Neural Networks and Attention Mechanism in Recurrent Neural Networks.\u003c\/p\u003e\u003cp\u003e.- Flexible Tails for Normalising Flows, with Application to the Modelling of Financial Return Data.\u003c\/p\u003e\u003cp\u003e.- Exploring Alternative Data for Nowcasting: A Case Study on US GDP using Topic Attention.\u003c\/p\u003e\u003cp\u003e.- Topology-Agnostic Detection of Temporal Money Laundering Flows in Billion-Scale Transactions.\u003c\/p\u003e\u003cp\u003e.- Boosting Credit Risk Data Quality using Machine Learning and eXplainable AI Techniques.\u003c\/p\u003e\u003cp\u003e.- Ensemble methods for Stock Market Prediction.\u003c\/p\u003e\u003cp\u003e\u003cstrong\u003e.- Workshop on Advancements in Federated Learning.\u003c\/strong\u003e\u003c\/p\u003e\u003cp\u003e.- Federated Learning with Neural Graphical Models.\u003c\/p\u003e\u003cp\u003e.- On improving accuracy in Federated Learning using GANs-based pre-training and Ensemble Learning.\u003c\/p\u003e\u003cp\u003e.- Re-evaluating the Privacy Benefit of Federated Learning.\u003c\/p\u003e\u003cp\u003e.- Parameterizing Federated Continual Learning for Reproducible Research.\u003c\/p\u003e","brand":"Springer","offers":[{"title":"Default Title","offer_id":53195416043863,"sku":"9783031746420","price":71.24,"currency_code":"GBP","in_stock":true}],"url":"https:\/\/bookcurl.com\/products\/machine-learning-and-principles-and-practice-of-knowledge-discovery-in-databases-9783031746420","provider":"Book Curl","version":"1.0","type":"link"}