Knowledge Science, Engineering and Management: Lecture Notes in Computer Science, cartea 14120
Editat de Zhi Jin, Yuncheng Jiang, Robert Andrei Buchmann, Yaxin Bi, Ana-Maria Ghiran, Wenjun Maen Limba Engleză Paperback – 10 aug 2023
| Toate formatele și edițiile | Preț | Express |
|---|---|---|
| Paperback (4) | 522.59 lei 6-8 săpt. | |
| Springer – 10 aug 2023 | 522.59 lei 6-8 săpt. | |
| Springer – 10 aug 2023 | 523.60 lei 6-8 săpt. | |
| Springer – 10 aug 2023 | 523.81 lei 6-8 săpt. | |
| Springer – 10 aug 2023 | 524.20 lei 6-8 săpt. |
Din seria Lecture Notes in Computer Science
- 20%
Preț: 558.53 lei - 20%
Preț: 571.88 lei - 20%
Preț: 675.83 lei - 20%
Preț: 1020.28 lei - 20%
Preț: 620.33 lei - 20%
Preț: 560.93 lei - 20%
Preț: 633.70 lei - 20%
Preț: 678.21 lei - 20%
Preț: 1359.66 lei - 20%
Preț: 560.93 lei - 20%
Preț: 733.68 lei - 20%
Preț: 793.92 lei - 15%
Preț: 558.12 lei - 20%
Preț: 793.92 lei - 20%
Preț: 560.93 lei - 20%
Preț: 748.63 lei - 20%
Preț: 562.49 lei - 20%
Preț: 1246.46 lei - 20%
Preț: 449.81 lei - 20%
Preț: 556.96 lei - 20%
Preț: 562.49 lei - 20%
Preț: 851.78 lei - 20%
Preț: 313.10 lei - 18%
Preț: 945.44 lei - 20%
Preț: 314.86 lei - 20%
Preț: 560.93 lei - 20%
Preț: 313.87 lei - 20%
Preț: 1033.45 lei - 20%
Preț: 563.29 lei - 20%
Preț: 733.68 lei - 20%
Preț: 1137.10 lei - 20%
Preț: 735.28 lei - 20%
Preț: 1079.23 lei - 20%
Preț: 560.11 lei - 20%
Preț: 791.54 lei - 15%
Preț: 672.87 lei - 20%
Preț: 1032.47 lei - 20%
Preț: 617.17 lei - 20%
Preț: 1022.15 lei - 20%
Preț: 984.64 lei - 20%
Preț: 620.33 lei - 20%
Preț: 979.25 lei - 20%
Preț: 402.28 lei - 20%
Preț: 316.28 lei - 20%
Preț: 636.06 lei - 20%
Preț: 320.24 lei - 20%
Preț: 328.94 lei
Preț: 524.20 lei
Preț vechi: 655.24 lei
-20%
Puncte Express: 786
Preț estimativ în valută:
92.69€ • 107.12$ • 80.08£
92.69€ • 107.12$ • 80.08£
Carte tipărită la comandă
Livrare economică 04-18 mai
Specificații
ISBN-13: 9783031402913
ISBN-10: 303140291X
Pagini: 496
Ilustrații: XXIV, 471 p. 124 illus., 112 illus. in color.
Dimensiuni: 155 x 235 x 27 mm
Greutate: 0.74 kg
Ediția:1st edition 2023
Editura: Springer
Colecția Lecture Notes in Computer Science
Seria Lecture Notes in Computer Science
Locul publicării:Cham, Switzerland
ISBN-10: 303140291X
Pagini: 496
Ilustrații: XXIV, 471 p. 124 illus., 112 illus. in color.
Dimensiuni: 155 x 235 x 27 mm
Greutate: 0.74 kg
Ediția:1st edition 2023
Editura: Springer
Colecția Lecture Notes in Computer Science
Seria Lecture Notes in Computer Science
Locul publicării:Cham, Switzerland
Cuprins
Emerging technologies for Knowledge science, engineering and management.- Federated Prompting and Chain-of-Thought Reasoning for Improving LLMs Answering.- Advancing Domain Adaptation of BERT by Learning Domain Term Semantics.- Deep Reinforcement Learning for Group-Aware Robot Navigation in Crowds.- An Enhanced Distributed Algorithm for Area Skyline Computation based on Apache Spark.- TCMCoRep: Traditional Chinese Medicine data mining with Contrastive Graph Representation Learning.- Local-Global Fusion Augmented Graph Contrastive Learning Based on Generative Models.- PRACM: Predictive Rewards for Actor-Critic with Mixing Function in Multi-Agent Reinforcement Learning.- A Cybersecurity Knowledge Graph Completion Method for Scalable Scenarios.- Research on remote sensing image classification based on Transfer learning and Data Augmentation.- Multivariate Long-Term Traffic Forecasting with Graph Convolutional Network and Historical Attention Mechanism.- Multi-hop Reading Comprehension Learning Method Based on Answer Contrastive Learning.- Importance-based Neuron Selective Distillation for Interference Mitigation in Multilingual Neural Machine Translation.- Are GPT Embeddings Useful for Ads and Recommendation?.- Modal interaction-enhanced Prompt Learning by transformer decoder for Vision-Language Models.- Unveiling Cybersecurity Threats from Online Chat Groups: A Triple Extraction Approach.- KSRL: Knowledge Selection based Reinforcement Learning for Knowledge-Grounded Dialogue.- Prototype-Augmented Contrastive Learning for Few-shot Unsupervised Domain Adaptation.- Style Augmentation and Domain-aware Parametric Contrastive Learning for Domain Generalization.- Recent Progress on Text Summarisation Based on BERT and GPT.- Ensemble Strategy Based on Deep Reinforcement Learning for Portfolio Optimization.- A Legal Multi-Choice Question Answering Model Based on BERT and Attention.- Offline Reinforcement Learning with Diffusion-Based Behavior Cloning Term.- Evolutionary Verbalizer Search for Prompt-based Few Shot Text Classification.- Graph Contrastive Learning Method with Sample Disparity Constraint and Feature Structure Graph for Node Classification.- Learning Category Discriminability for Active Domain Adaptation.- Multi-Level Contrastive Learning for Commonsense Question Answering.- Efficient Hash Coding for Image Retrieval based on Improved Center Generation and Contrastive Pre-training Knowledge Model.- Univarite Time Series Forecasting via Interactive Learning.- Task Inference for Offline Meta Reinforcement Learning via Latent Shared Knowledge.- A Quantitative Spectra Analysis Framework Combining Mixup and Band Attention for Predicting Soluble Solid Content of Blueberries.- Contextualized Hybrid Prompt-Tuning for Generation-Based Event Extraction.- udPINNs: An Enhanced PDE Solving Algorithm Incorporating Domain of Dependence Knowledge.- Joint Community and Structural Hole Spanner Detection via Graph Contrastive Learning.- A Reinforcement Learning-based Approach for Continuous Knowledge Graph Construction.- A Multifactorial Evolutionary Algorithm based on Model Knowledge Transfer.- Knowledge Leadership, AI Technology Adoption and Big Data Application Ability.- RFLSem: A lightweight model for textual sentiment analysis.