01540nam 2200349Ia 450 99638642550331620231213232721.0(CKB)4940000000077137(EEBO)2240968159(OCoLC)ocn124064261e(OCoLC)124064261(EXLCZ)99494000000007713720070508d1683 uy 0engurbn#|||a|bb|Regiae grammaticae clavis: or, Two parsing tables[electronic resource] Being a singular contrivance to facilitate the performance of that profitable exercise of parsing or proving Latine by grammar rule. Designed for the aid and benefit (and therefore tendred to the perusal) of young grammarians. /By William RonksleyLondon, Printed for John Kidgell ...1683[8], 103 pDivisional t.p. on p. [5]: Tabula prima: the first table; directing to the rule for the gender of anomaly of any noun ...Divisional t.p. on p. 31: Tabula secunda, the second table; containing most of the regent-words ...Text is mixed Latin and English.Reproduction of original in the University of Toronto Library.eebo-0180Latin languageGrammarEarly works to 1800Latin languageGrammarRonksley William1006014UMIUMIBOOK996386425503316Regiae grammaticae clavis: or, Two parsing tables2314437UNISA05456nam 22006375 450 991087219590332120250806170448.03-031-63800-X10.1007/978-3-031-63800-8(CKB)32775437300041(MiAaPQ)EBC31523152(Au-PeEL)EBL31523152(DE-He213)978-3-031-63800-8(EXLCZ)993277543730004120240710d2024 u| 0engur|||||||||||txtrdacontentcrdamediacrrdacarrierExplainable Artificial Intelligence Second World Conference, xAI 2024, Valletta, Malta, July 17–19, 2024, Proceedings, Part III /edited by Luca Longo, Sebastian Lapuschkin, Christin Seifert1st ed. 2024.Cham :Springer Nature Switzerland :Imprint: Springer,2024.1 online resource (471 pages)Communications in Computer and Information Science,1865-0937 ;21553-031-63799-2 -- 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.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.Communications in Computer and Information Science,1865-0937 ;2155Artificial intelligenceNatural language processing (Computer science)Application softwareComputer networksArtificial IntelligenceNatural Language Processing (NLP)Computer and Information Systems ApplicationsComputer Communication NetworksArtificial intelligence.Natural language processing (Computer science)Application software.Computer networks.Artificial Intelligence.Natural Language Processing (NLP).Computer and Information Systems Applications.Computer Communication Networks.006.3Longo Luca1337583Lapuschkin Sebastian1744132Seifert Christin1744133MiAaPQMiAaPQMiAaPQBOOK9910872195903321Explainable Artificial Intelligence4173978UNINA