LMQ-Sketch: Lagom Multi-Query Sketch for High-Rate Online Analytics
arxiv.orgยท2d
๐ŸŒŠStreaming Algorithms
A Briefing on Logistic Regression
blog.engora.comยท2hยท
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๐Ÿง Machine Learning
Machine Learning Fundamentals: accuracy with python
dev.toยท23hยท
Discuss: DEV
๐Ÿ‘๏ธObservatory Systems
Survey Statistics: Poststratification ?
statmodeling.stat.columbia.eduยท18h
๐ŸŽฏArithmetic Coding Theory
ML in the Home
blog.raymond.burkholder.netยท1d
๐Ÿ“ˆTime Series
Ask HN: Feedback on "QSS" โ€“ A Quantized Vector Search Engine in C
news.ycombinator.comยท1dยท
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๐Ÿ—‚๏ธVector Databases
UltraSketchLLM: Saliency-Driven Sketching for Ultra-Low Bit LLM Compression
arxiv.orgยท1d
๐Ÿ—œ๏ธLZW Variants
Probabilistic and reinforced mining of association rules
arxiv.orgยท1d
๐Ÿง Learned Indexes
Show HN: Logcat.ai โ€“ AI-powered observability for Operating Systems | Free Beta
logcat.aiยท21hยท
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๐Ÿ”eBPF
A large deviation view of \emph{stationarized} fully lifted blirp interpolation
arxiv.orgยท10h
๐Ÿ“Compression Bounds
Greedy Is Good. Less Greedy May Be Better
gojiberries.ioยท13hยท
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๐ŸงฎKolmogorov Complexity
Plan for Speed -- Dilated Scheduling for Masked Diffusion Language Models
arxiv.orgยท10h
๐Ÿ’ปLocal LLMs
How much slower is random access, really?
samestep.comยท1dยท
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๐Ÿ“ผTape Encoding
Flame Graph Performance Truth Analysis๏ผˆ1750839255230100๏ผ‰
dev.toยท6hยท
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โšกPerformance Tools
Simple API monitoring, analytics and request logging for Chi, Echo, Fiber, and Gin
reddit.comยท1dยท
Discuss: r/golang
๐ŸŒ€Brotli Internals
Online high-precision prediction method for injection molding product weight by integrating time series/non-time series mixed features and feature attention mec...
arxiv.orgยท10h
๐Ÿง Machine Learning
Fully lifted \emph{blirp} interpolation -- a large deviation view
arxiv.orgยท10h
๐ŸŒ€Fractal Compression
The first CNN for playing Scrabble โ€“ a game of imperfect information
cesardelsolar.comยท2dยท
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๐Ÿ”ฒCellular Automata
Black-Box Test Code Fault Localization Driven by Large Language Models and Execution Estimation
arxiv.orgยท10h
๐Ÿ”Concolic Testing
What LLMs Know About Their Users
schneier.comยท3h
๐Ÿ’ปLocal LLMs