Explore Microsoft's innovative approach to query optimization in production environments, addressing challenges with general-purpose optimization and introducing specialized cloud-based optimizers. Learn about the implementation details, experiments conducted, and the solution proposed. Discover how

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The evaluation strategy used for machine learning models significantly impacts their interpretation and performance. This study explores different evaluation methods and their implications for understanding climate-crop dynamics using explainable machine learning approaches. The strategy involves tr

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The paper delves into the necessity for Explainable AI driven by regulations such as the GDPR, which mandates explanations for algorithmic decisions. It discusses the debate surrounding the existence of a legally binding right to explanation and the complexities of accommodating algorithmic machines

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Discover how XAI is enhancing transparency, building trust, and driving adoption in industries like healthcare, finance, and legal sectors.\n

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This study explores the use of Chain of Thought Prompting (CoT) for few-shot intent classification using large language models. The approach involves a series of reasoning steps to better understand user intent, leading to improved performance and explainable results compared to traditional promptin

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This article explores the concept of generating interpretable, diverse, and plausible counterfactual explanations within explainable AI (XAI). It highlights the challenges with current methods, introduces an instance-guided approach, and emphasizes the importance of good counterfactuals. The discuss

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The research presented at the 33rd AAAI Conference on Artificial Intelligence focuses on developing an explainable deep model for recommendation systems. It addresses challenges in extracting explicit features from noisy data and proposes a Deep Explicit Attentive Multi-View Learning Model. This mod

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Catholics value revelation as a means through which God reveals aspects of His nature. Natural revelation points to God's existence through the world, while special revelation is seen in the Bible. Jesus Christ is central to Catholic belief as the ultimate revelation of God, showing His love, forgiv

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Explainable AI (XAI) addresses the need for human-understandable AI models, contrasting with black box approaches. Intelligent gap filling for CCI ECV data is crucial but lacks efficient methods. Machine Learning can enhance EO data analysis with XAI insights, necessitating collaboration between dom

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Explainable AI (XAI) bridges the gap between complex AI models and human understanding by providing insights into how and why decisions are made. It matters because XAI can prevent errors, biases, and adversarial attacks in AI systems. Complexity in AI models affects accuracy and explainability, wit

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Explore how machine learning methods are applied to analyze São Paulo transit data, focusing on factors affecting bus service reliability measures. The study delves into quantifying and identifying relevant factors impacting service reliability across different levels such as stops, routes, and the

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The Evolution of AI from prehistory to the modern era, exploring key milestones in the development of Artificial Intelligence. It covers the transition from early Neural Networks to the current focus on Explainable AI, highlighting DARPA's XAI program and techniques for achieving a balance between p

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Exploring the intersection of Human-Computer Interaction and Artificial Intelligence to enhance understanding and trust in smart machines. The workshop delves into explainable AI, psychological models, and the importance of effective explanations in fostering trust. A naturalistic study reviewed cas

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