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Philosophy, Science and Religion: Religion and Science
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Explore the synergistic potential between humans and LLMs in decision-making tasks, examining active learning, ML fairness, and collaborative approaches to AI implementation.
Explore evaluation methods for information systems that address misinformation, fairness, and bias beyond traditional relevance metrics, with practical insights into quantitative measurement approaches.
Dive into quantum annealing techniques for feature selection and clustering through hands-on demonstrations and practical implementations for advanced data analysis tasks.
Explore how information retrieval systems adapt to evolving web content and search queries, examining temporal performance decline and necessary updates through the LongEval-Retrieval track analysis.
Dive into the evaluation frameworks for open web search applications, focusing on TIREx implementation, Docker integration, and practical approaches to building reproducible search engine solutions.
Explore patterns of online misinformation and social misbehavior, focusing on fake news dissemination, political campaigns, and hate speech analysis through data-driven research and network dynamics.
Explore cutting-edge research at UFMG Brazil combining AI, Information Retrieval, and NLP, with applications in law, health, and scientometrics through diverse machine learning techniques.
Discover how Microsoft's framework compiles SQL to tensor abstractions, enabling efficient database analytics on GPUs and exploring the fusion of SQL with machine learning capabilities.
Explore the challenges and solutions of User-Defined Functions in relational databases, focusing on YeSQL's innovative approach to seamlessly integrate Python UDFs with enhanced performance and functionality.
Explore ethical considerations in data-driven systems, focusing on responsible data collection, preparation, and lifecycle management for building fair and interpretable AI solutions.
Dive into AI-powered cloud performance optimization techniques, exploring how modern applications can achieve peak efficiency through automated tuning and machine learning approaches.
Explore the principles of explainable AI, from feature-based to data-driven models, examining key algorithms like LIME and Shapley while understanding their broader societal impact and applications in search systems.
Discover how to build and evaluate privacy-focused web search engines, exploring dynamic test collections for continuous evaluation and practical insights on creating scalable solutions with limited resources.
Explore the science of digital nudging and how personalized, context-aware suggestions can effectively influence behavioral change while respecting ethical boundaries and user privacy.
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