{"product_id":"advances-and-trends-in-artificial-intelligence-theory-and-applications-ebook","title":"Advances and Trends in Artificial Intelligence. Theory and Applications","description":"\u003cp\u003e\u003cstrong\u003e.- Reinforcement Learning.\u003c\/strong\u003e\u003c\/p\u003e\n\u003cp\u003e.- An Enhanced Preference-Based Reinforcement Learning Framework for Autonomous System.\u003c\/p\u003e\n\u003cp\u003e.- Reinforcement Learning based Iterated Greedy for Parallel Machine Scheduling with Weighted Earliness Tardiness.\u003c\/p\u003e\n\u003cp\u003e.- VMD-IMF Enhanced Hyper Graph Attention Module Based Reinforcement Learning For Portfolio Optimization.\u003c\/p\u003e\n\u003cp\u003e.- A reinforcement learning based framework to the facility layout problem.\u003c\/p\u003e\n\u003cp\u003e\u003cstrong\u003e.- Optimization.\u003c\/strong\u003e\u003c\/p\u003e\n\u003cp\u003e.- Bayesian Optimization for Fine-Tuning an AI Solver: Application to Preventive Maintenance Scheduling Problems.\u003c\/p\u003e\n\u003cp\u003e.- Domain Generalization through Domain-Expert Risk Assessment.\u003c\/p\u003e\n\u003cp\u003e.- Enhanced Optimization Space Learning: Towards Real-Time Compiler Optimization.\u003c\/p\u003e\n\u003cp\u003e.- Optimizing Feature Selection Binary Peacock Algorithm with improved movement strategy.\u003c\/p\u003e\n\u003cp\u003e\u003cstrong\u003e.- Natural Language Processing.\u003c\/strong\u003e\u003c\/p\u003e\n\u003cp\u003e.- Apply TF-IDF and LDA to Explore Topics and Related Trends in Electric Vehicle Reviews.\u003c\/p\u003e\n\u003cp\u003e.- Identifying Fake Reviews and Their Implications Using BERT and LDA: A Case Study of Online Shopping Website Reviews.\u003c\/p\u003e\n\u003cp\u003e.- A Lightweight and Efficient Punctuation and Word Casing Prediction Model for On Device Streaming ASR.\u003c\/p\u003e\n\u003cp\u003e.- SYNCAD: Synchronised Yields from Narrative Cross Modal Audio and Data.\u003c\/p\u003e\n\u003cp\u003e.- MultiGAU: Real Time Sign Language Generation using Multimodal Gated Attention.\u003c\/p\u003e\n\u003cp\u003e.- Classification of Approval Desires and Analysis of Emotional and Linguistic Features in SNS Posts Using Generative AI.\u003c\/p\u003e\n\u003cp\u003e\u003cstrong\u003e.- Multi-Agent.\u003c\/strong\u003e\u003c\/p\u003e\n\u003cp\u003e.- Hierarchical Multi-Agent Reinforcement Learning with Epistemic Priors for Scalable Communicationless Coordination of Teamable Agents.\u003c\/p\u003e\n\u003cp\u003e.- DynaMIX: Sample-Efficient Multi Agent Reinforcement Learning with Multi-Step Temporal Forward Dynamics Modeling.\u003c\/p\u003e\n\u003cp\u003e.- Automated Issue Hierarchy Generation for Improved Automated Negotiation Outcomes.\u003c\/p\u003e\n\u003cp\u003e\u003cstrong\u003e.- Machine Learning and Decision Making.\u003c\/strong\u003e\u003c\/p\u003e\n\u003cp\u003e.- Distribution Variance for Surrogate Weights in Multi-Criteria Decision Analysis.\u003c\/p\u003e\n\u003cp\u003e.- Bridging the Trust Gap: Leveraging Explainable AI for Personalized E-Commerce Recommendations.\u003c\/p\u003e\n\u003cp\u003e.- A clustering method based on hesitant difference granularity.\u003c\/p\u003e\n\u003cp\u003e.- Evaluation of Efficient AI for the Edge: Insights from Deep Neural Networks Model Compression Techniques Applied to Occupancy Detection.\u003c\/p\u003e\n\u003cp\u003e.- LSTM-based Proactive Scheduling of Stream Applications in Edge\/Cloud Environments.\u003c\/p\u003e\n\u003cp\u003e.- Uncertainty Quantification Of Multimodal Models.\u003c\/p\u003e\n\u003cp\u003e\u003cstrong\u003e.- Knowledge Representation.\u003c\/strong\u003e\u003c\/p\u003e\n\u003cp\u003e.- Automating OntoClean Ontology Verification.\u003c\/p\u003e\n\u003cp\u003e.- Automating OntoClean - Subsumption Hierarchy Construction.\u003c\/p\u003e\n\u003cp\u003e.- Possibilistic Reasoning with Fuzzy Formal Contexts: An Extended Abstract.\u003c\/p\u003e\n\u003cp\u003e.- A Strategy for Implementing Garbage Detection in Ontology Completion using Description Logics.\u003c\/p\u003e\n\u003cp\u003e\u003cstrong\u003e.- Data Engineering.\u003c\/strong\u003e\u003c\/p\u003e\n\u003cp\u003e.- Uncertainty-based Instance-Dependent Noisy Label Datasets Generation.\u003c\/p\u003e\n\u003cp\u003e.- Guided by Uncertainty: Semi-supervised Domain Adaptation with Curriculum and Contrastive Learning.\u003c\/p\u003e\n\u003cp\u003e.- Linking Data Meaningfully: Identifying Meaningful Keys and Foreign Keys from Data.\u003c\/p\u003e\n\u003cp\u003e.- CAMI: A missing value imputation method based on causal discovery and self-attention.\u003c\/p\u003e\n\u003cp\u003e.- MDR: An Ontology Vocabulary and Registry Service for Dataset Catalogs.\u003c\/p\u003e\n\u003cp\u003e.- A-REACT: Adaptive Resampling and Active Classification for Thresholded Anomalies.\u003c\/p\u003e\n\u003cp\u003e.- DistResampleR-Lite: Light Distributed Resampler for Imbalanced Regression Problems.\u003c\/p\u003e\n\u003cp\u003e.- Fast HSIC-based tests for random processes.\u003c\/p\u003e\n\u003cp\u003e\u003cstrong\u003e.- Large Language Model.\u003c\/strong\u003e\u003c\/p\u003e\n\u003cp\u003e.- Exploring the Efficacy of Large Language Models in Predicting Chemical Toxicity.\u003c\/p\u003e\n\u003cp\u003e.- Towards Predicting Complex Carpooling Trajectories with Context-Augmented BERT LLM in Chaotic Environments.\u003c\/p\u003e\n\u003cp\u003e.- LLM-base MaSE, A Software Development Framework for Developing Multi-Agent Systems.\u003c\/p\u003e\n\u003cp\u003e\u003cstrong\u003e.- Computer Vision.\u003c\/strong\u003e\u003c\/p\u003e\n\u003cp\u003e.- WeldViT: A Lightweight Network for Online Identification of Multi-Label Welding Defects.\u003c\/p\u003e\n\u003cp\u003e.- Impact of Replay Ratios on Performance and Efficiency in Continual Learning for Skeleton-based Action Recognition.\u003c\/p\u003e\n\u003cp\u003e.- Extending YOLO for Feature-Based Classification Through Numerical-to-Image Transformation.\u003c\/p\u003e\n\u003cp\u003e.- Lost in the Noise: Evading and Detecting Backdoors in Conditional Diffusion Models.\u003c\/p\u003e\n\u003cp\u003e. SkinPalNet: An Advanced Ensemble Model for Skin Cancer Diagnosis with Computer Vision Approach.\u003c\/p\u003e\n\u003cp\u003e.- Enhancing Minimarket Customer Experience through YOLOv8-Powered Checkout Systems.\u003c\/p\u003e\n\u003cp\u003e.- Brain Tumor MRI Interpretation: Towards a Benchmark for Medical Visual Question Answering.\u003c\/p\u003e","brand":"Hamido Fujita","offers":[{"title":"Default Title","offer_id":53653328625991,"sku":"9789819688890","price":85.59,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0920\/5455\/2903\/files\/advances-and-trends-in-artificial-intelligence-the-ebook-cover.webp?v=1775397343","url":"https:\/\/www.cinebuch.de\/products\/advances-and-trends-in-artificial-intelligence-theory-and-applications-ebook","provider":"CineBuch","version":"1.0","type":"link"}