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Scaling de-duplication in WorldCat: Balancing AI innovation with cataloging care | OCLC

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The fundamental shift in de-duplication Historically, de-duplication has relied on deterministic algorithms and manual effort on the part of catalogers and OCLC staff. While effective, these methods have limits. and its affiliates Privacy statement Cookie notice Cookie settings Accessibility statement ISO 27001 Certificate

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Inductive biases of neural network modularity in spatial navigation

ML @ CMU

In practice, our algorithm is off-policy and incorporates mechanisms such as two critic networks and target networks as in TD3 ( fujimoto et al., 2020 ) to systematically quantify behavioral accuracy. 2018 ) to enhance training (see Materials and Methods in Zhang et al.,

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Lessons Learned After 6.5 Years Of Machine Learning

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Coding ML algorithms, debugging obscure data issues, crafting a hypothesis — it all demands deep work. The world’s leading publication for data science, data analytics, data engineering, machine learning, and artificial intelligence professionals. What does is the ability to focus deeply.

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I Won $10,000 in a Machine Learning Competition — Here’s My Complete Strategy

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Conclusion This competition reinforced something I’ve known for a while: Success in machine learning isn’t about having the fanciest tools or the most complex algorithms. The world’s leading publication for data science, data analytics, data engineering, machine learning, and artificial intelligence professionals.

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Training AI to Detect Disease: Stand Up To Cancer’s Julian Adams

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Past Issues Webinars & Podcasts Upcoming Events Video Archive Podcasts Me, Myself, and AI Search Store Sign In Subscribe — 22% off Me, Myself, and AI Episode 1107 Training AI to Detect Disease: Stand Up To Cancer’s Julian Adams June 11, 2025 / The nonprofit uses artificial intelligence to aid in cancer detection.

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DeepSeek R2 is coming fast: Can the West keep up?

Dataconomy

Liang, who began his career in smart imaging and later managed a research team, was praised for hiring top algorithm engineers and fostering a collaborative environment. The firm allocated 70% of its revenue towards AI research, building two supercomputing AI clusters, including one consisting of 10,000 Nvidia A100 chips during 2020 and 2021.

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3D Gaussian Splatting vs NeRF: The End Game of 3D Reconstruction?

PyImageSearch

Okay, here it is: The 3-Way Process of Gaussian Splatting: Whats interesting is how we begin from Photogrammetry Now, the actual process isnt so easy to get, its actually explained here: The Gaussian Splatting Algorithm (source: Kerbl et al., Essentially, you send 30+ input images to an SfM algorithm, and it returns a point cloud.