DRIFT: Data Reduction via Informative Feature Transformation- Generalization Begins Before Deep Learning starts
arxiv.org·21h
🧠Machine Learning
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🔃Feed Algorithms
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🌊Stream Processing
Computer-vision research powers surveillance technology
nature.com·8h·
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🔎OSINT Techniques
Engagement, Monetization and the Impact of AI Take Center Stage at NATPE Budapest
hollywoodreporter.com·1h
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The Overlooked Power of Rails in the Age of AI
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thenewstack.io·11h
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kdnuggets.com·13h
🎙️Whisper
2025-06-24: GPU Hours Granted on Hypothesis Generation by Oak Ridge Leadership Computing Facility
ws-dl.blogspot.com·1d·
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🏴󠁧󠁢󠁳󠁣󠁴󠁿Scottish Computing
LLMs for Customized Marketing Content Generation and Evaluation at Scale
arxiv.org·1d
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Greedy Is Good. Less Greedy May Be Better
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🧮Kolmogorov Complexity
An All-Around Better Horse
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🧠Knowledge Management
Machine Learning Fundamentals: active learning project
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🧠Machine Learning
Alleviating User-Sensitive bias with Fair Generative Sequential Recommendation Model
arxiv.org·21h
🎛️Feed Filtering
Predictive Analytics for Collaborators Answers, Code Quality, and Dropout on Stack Overflow
arxiv.org·1d
📊Feed Optimization
Google AI exec: “The mistake would be thinking this is hype.”
freethink.com·3h
🌀Brotli Internals
Show HN: Requests-Based Google Maps Scraper
apify.com·4h·
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🔍BitFunnel
GLIMPSE: Gradient-Layer Importance Mapping for Prompted Visual Saliency Explanation for Generative LVLMs
arxiv.org·21h
📊Learned Metrics
Machine Learning Fundamentals: active learning with python
dev.to·7h·
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🧠Machine Learning
Mapping the Evolution of Research Contributions using KnoVo
arxiv.org·1d
📊Citation Graphs