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๐Ÿ“Š Count-Min Sketch

Frequency Estimation, Stream Analytics, Space Efficiency, Approximate Counting

The first CNN for playing Scrabble โ€“ a game of imperfect information
cesardelsolar.comยท2dยท
Discuss: Hacker News
๐Ÿ”ฒCellular Automata
Black-Box Test Code Fault Localization Driven by Large Language Models and Execution Estimation
arxiv.orgยท14h
๐Ÿ”Concolic Testing
Driving cost-efficiency and speed in claims data processing with Amazon Nova Micro and Amazon Nova Lite
aws.amazon.comยท1h
๐ŸŒŠStream Processing
What LLMs Know About Their Users
schneier.comยท7hยท
Discuss: Hacker News
๐Ÿ’ปLocal LLMs
DRIFT: Data Reduction via Informative Feature Transformation- Generalization Begins Before Deep Learning starts
arxiv.orgยท14h
๐Ÿง Machine Learning
Oreo's Top K Treats (Bucket Sort)
dev.toยท6hยท
Discuss: DEV
๐ŸŒŠStreaming Algorithms
Small language model for secrets detection
wiz.ioยท2dยท
Discuss: Hacker News
๐Ÿ’ปLocal LLMs
SlimMoE: Structured Compression of Large MoE Models via Expert Slimming and Distillation
arxiv.orgยท1d
โšกModern Compression
Vibe Coding a Speed Reading App with Python in Just 15 Minutes
kdnuggets.comยท4h
๐Ÿ—œ๏ธLZSS Variants
Contextualizing SUTRA: Advancements in Multilingual & Efficient LLMs
hackernoon.comยท2h
๐Ÿ’ปLocal LLMs
Evaluating Rare Disease Diagnostic Performance in Symptom Checkers: A Synthetic Vignette Simulation Approach
arxiv.orgยท14h
๐ŸŒธBloom Variants
Efficient stream-based Max-Min diversification with minimal failure rate
arxiv.orgยท1d
๐ŸŒŠStreaming Algorithms
Using Wavelets and Clustering to Predict Odd or Even Numbers: An Overengineered Approach with Pretty (But Confusing) Plots
dev.toยท5hยท
Discuss: DEV
๐Ÿง Machine Learning
Scalable Machine Learning Algorithms using Path Signatures
arxiv.orgยท1d
๐Ÿง Machine Learning
No pre-filtering in pgvector means reduced ANN recall
dev.toยท1dยท
Discuss: DEV
๐Ÿ—‚๏ธVector Databases
Building a Go Concurrency Task Scheduler: Efficient Task Processing Unleashed
dev.toยท17hยท
Discuss: DEV
๐ŸŒŠStream Processing
An Expanded Benchmark that Rediscovers and Affirms the Edge of Uncertainty Sampling for Active Learning in Tabular Datasets
arxiv.orgยท1d
๐Ÿ“Range Queries
Programming, Not Prompting: A Hands-On Guide to DSPy
towardsdatascience.comยท1d
๐ŸงฎZ3 Solver
Fast Rate Information-theoretic Bounds on Generalization Errors
arxiv.orgยท1d
โง—Information Bottleneck
Alleviating User-Sensitive bias with Fair Generative Sequential Recommendation Model
arxiv.orgยท14h
๐ŸŽ›๏ธFeed Filtering
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