What are the limitations of current benchmarking practices?

Key network metrics and information-theoretic measures were extracted to classify PD patients and healthy controls (HC), using deep learning models, with ... ... Artificial Intelligence (AI) in transforming business. Covering key areas like machine learning, natural language processing, computer vision, and robotics ... We investigates how an RL agent could influence other learning agents by providing information in mixed-motive settings. Sep 14, 2023 ... In active learning, the informative data points are selected using query strategies instead of a pre-defined labeled dataset. Then, an annotator ... Oct 21, 2024 ... Abbas Saad Alatrany, Wasiq Khan, Abir Hussain, Hoshang Kolivand, and Dhiya Al-Jumeily. 2024. An explainable machine learning approach for ... Research topics. Data mining. Machine learning. Information security. Supply chain management. Healthcare information systems. In the Media. A worker gestures ... PhD, Information, University of Michigan. Research focus: Trustworthy machine learning, regulatable machine learning; data-centric AI; machine learning on ... Getting Personal: A Deep Learning Artifact for Text-Based Measurement of Personality ... Expl(AI)ned: The Impact of Explainable Artificial Intelligence on Users' ... Oct 10, 2023 ... Machine learning can accurately identify 83% to 99.8% of data waste; deep learning models are particularly promising, with accuracy ranging from ... Nov 14, 2024 ... Register Today for GAP Informational Webinar ... machine learning, large language models, or generative AI technologies and infrastructures.