Explainable Artificial Intelligence (Record no. 88538)
[ view plain ]
| 000 -LEADER | |
|---|---|
| fixed length control field | 05741nam a22005895i 4500 |
| 001 - CONTROL NUMBER | |
| control field | 978-3-031-63800-8 |
| 005 - DATE AND TIME OF LATEST TRANSACTION | |
| control field | 20240730172748.0 |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION | |
| fixed length control field | 240710s2024 sz | s |||| 0|eng d |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER | |
| ISBN | 9783031638008 |
| -- | 978-3-031-63800-8 |
| 082 04 - CLASSIFICATION NUMBER | |
| Call Number | 006.3 |
| 245 10 - TITLE STATEMENT | |
| Title | Explainable Artificial Intelligence |
| Sub Title | Second World Conference, xAI 2024, Valletta, Malta, July 17-19, 2024, Proceedings, Part III / |
| 250 ## - EDITION STATEMENT | |
| Edition statement | 1st ed. 2024. |
| 300 ## - PHYSICAL DESCRIPTION | |
| Number of Pages | XVII, 456 p. 130 illus., 103 illus. in color. |
| 490 1# - SERIES STATEMENT | |
| Series statement | Communications in Computer and Information Science, |
| 505 0# - FORMATTED CONTENTS NOTE | |
| Remark 2 | -- Counterfactual explanations and causality for eXplainable AI. -- Sub-SpaCE: Subsequence-based Sparse Counterfactual Explanations for Time Series Classification Problems. -- Human-in-the-loop Personalized Counterfactual Recourse. -- COIN: Counterfactual inpainting for weakly supervised semantic segmentation for medical images. -- Enhancing Counterfactual Explanation Search with Diffusion Distance and Directional Coherence. -- CountARFactuals -- Generating plausible model-agnostic counterfactual explanations with adversarial random forests. -- Causality-Aware Local Interpretable Model-Agnostic Explanations. -- Evaluating the Faithfulness of Causality in Saliency-based Explanations of Deep Learning Models for Temporal Colour Constancy. -- CAGE: Causality-Aware Shapley Value for Global Explanations. -- Fairness, trust, privacy, security, accountability and actionability in eXplainable AI. -- Exploring the Reliability of SHAP Values in Reinforcement Learning. -- Categorical Foundation of Explainable AI: A Unifying Theory. -- Investigating Calibrated Classification Scores through the Lens of Interpretability. -- XentricAI: A Gesture Sensing Calibration Approach through Explainable and User-Centric AI. -- Toward Understanding the Disagreement Problem in Neural Network Feature Attribution. -- ConformaSight: Conformal Prediction-Based Global and Model-Agnostic Explainability Framework. -- Differential Privacy for Anomaly Detection: Analyzing the Trade-off Between Privacy and Explainability. -- Blockchain for Ethical & Transparent Generative AI Utilization by Banking & Finance Lawyers. -- Multi-modal Machine learning model for Interpretable Mobile Malware Classification. -- Explainable Fraud Detection with Deep Symbolic Classification. -- Better Luck Next Time: About Robust Recourse in Binary Allocation Problems. -- Towards Non-Adversarial Algorithmic Recourse. -- Communicating Uncertainty in Machine Learning Explanations: A Visualization Analytics Approach for Predictive Process Monitoring. -- XAI for Time Series Classification: Evaluating the Benefits of Model Inspection for End-Users. |
| 520 ## - SUMMARY, ETC. | |
| Summary, etc | This four-volume set constitutes the refereed proceedings of the Second World Conference on Explainable Artificial Intelligence, xAI 2024, held in Valletta, Malta, during July 17-19, 2024. The 95 full papers presented were carefully reviewed and selected from 204 submissions. The conference papers are organized in topical sections on: Part I - intrinsically interpretable XAI and concept-based global explainability; generative explainable AI and verifiability; notion, metrics, evaluation and benchmarking for XAI. Part II - XAI for graphs and computer vision; logic, reasoning, and rule-based explainable AI; model-agnostic and statistical methods for eXplainable AI. Part III - counterfactual explanations and causality for eXplainable AI; fairness, trust, privacy, security, accountability and actionability in eXplainable AI. Part IV - explainable AI in healthcare and computational neuroscience; explainable AI for improved human-computer interaction and software engineering for explainability; applications of explainable artificial intelligence. |
| 700 1# - AUTHOR 2 | |
| Author 2 | Longo, Luca. |
| 700 1# - AUTHOR 2 | |
| Author 2 | Lapuschkin, Sebastian. |
| 700 1# - AUTHOR 2 | |
| Author 2 | Seifert, Christin. |
| 856 40 - ELECTRONIC LOCATION AND ACCESS | |
| Uniform Resource Identifier | https://doi.org/10.1007/978-3-031-63800-8 |
| 942 ## - ADDED ENTRY ELEMENTS (KOHA) | |
| Koha item type | eBooks |
| 264 #1 - | |
| -- | Cham : |
| -- | Springer Nature Switzerland : |
| -- | Imprint: Springer, |
| -- | 2024. |
| 336 ## - | |
| -- | text |
| -- | txt |
| -- | rdacontent |
| 337 ## - | |
| -- | computer |
| -- | c |
| -- | rdamedia |
| 338 ## - | |
| -- | online resource |
| -- | cr |
| -- | rdacarrier |
| 347 ## - | |
| -- | text file |
| -- | |
| -- | rda |
| 650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
| -- | Artificial intelligence. |
| 650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
| -- | Natural language processing (Computer science). |
| 650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
| -- | Application software. |
| 650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
| -- | Computer networks . |
| 650 14 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
| -- | Artificial Intelligence. |
| 650 24 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
| -- | Natural Language Processing (NLP). |
| 650 24 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
| -- | Computer and Information Systems Applications. |
| 650 24 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
| -- | Computer Communication Networks. |
| 700 1# - AUTHOR 2 | |
| -- | (orcid) |
| -- | 0000-0002-2718-5426 |
| 700 1# - AUTHOR 2 | |
| -- | (orcid) |
| -- | 0000-0002-0762-7258 |
| 700 1# - AUTHOR 2 | |
| -- | (orcid) |
| -- | 0000-0002-6776-3868 |
| 830 #0 - SERIES ADDED ENTRY--UNIFORM TITLE | |
| -- | 1865-0937 ; |
| 912 ## - | |
| -- | ZDB-2-SCS |
| 912 ## - | |
| -- | ZDB-2-SXCS |
No items available.