AppBITS: Sorted Seems Moribund
tidbits.comยท6h
๐Ÿ”ƒFeed Algorithms
A Briefing on Logistic Regression
blog.engora.comยท9hยท
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๐Ÿง Machine Learning
DSPy for Rubyists
github.comยท1dยท
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๐ŸŒ€Brotli Internals
The most efficient algorithm for detecting claws in general graphs, with a runtime of O(m ฮ”) โ€” where m is the number of edges and ฮ” is the maximum degree โ€” is n...
dev.toยท1dยท
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๐Ÿ”—Topological Sorting
Optimal Parallel Algorithms for Convex Hulls in 2D and 3D under Noisy Primitive Operations
arxiv.orgยท1d
๐Ÿ“ŠComputational Geometry
The Power of Strong Linearizability: the Difficulty of Consistent Refereeing
arxiv.orgยท1d
๐ŸŽฏPerformance Proofs
DRIFT: Data Reduction via Informative Feature Transformation- Generalization Begins Before Deep Learning starts
arxiv.orgยท18h
๐Ÿง Machine Learning
UltraSketchLLM: Saliency-Driven Sketching for Ultra-Low Bit LLM Compression
arxiv.orgยท1d
๐Ÿ—œ๏ธLZW Variants
Alleviating User-Sensitive bias with Fair Generative Sequential Recommendation Model
arxiv.orgยท18h
๐ŸŽ›๏ธFeed Filtering
The collective waste caused by poor documentation
shanrauf.comยท20hยท
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๐Ÿ“ฆDeflate
When Data Becomes a Bottleneck: Why Smart People Still Struggle to Get Answers
dev.toยท10hยท
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๐ŸŒŠStream Processing
๐Ÿง  Solving LeetCode Until I Become Top 1% โ€” Day `30`
dev.toยท14hยท
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๐Ÿ“Error Bounds
Machine Learning Fundamentals: active learning
dev.toยท1dยท
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๐Ÿค–Grammar Induction
Machine Learning Fundamentals: active learning project
dev.toยท6hยท
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๐Ÿง Machine Learning
Why Agentic Flows Need Distributed-Systems Discipline
temporal.ioยท1dยท
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โš™๏ธTLA+
Black-Box Test Code Fault Localization Driven by Large Language Models and Execution Estimation
arxiv.orgยท18h
๐Ÿ”Concolic Testing
Geometry-aware Distance Measure for Diverse Hierarchical Structures in Hyperbolic Spaces
arxiv.orgยท1d
๐ŸŒ€Hyperbolic Geometry
On the convergence of computational methods for the online bin stretching problem
arxiv.orgยท1d
๐ŸŽฏPerformance Proofs
Fast and Distributed Equivariant Graph Neural Networks by Virtual Node Learning
arxiv.orgยท18h
๐ŸŒ€Riemannian Computing
A Principled Approach to Randomized Selection under Uncertainty
arxiv.orgยท18h
๐ŸŒธBloom Variants