🔍 Min-Hash

Locality Sensitive Hashing, Jaccard Similarity, Duplicate Detection, Document Clustering

Web fingerprinting is worse than I thought
bitestring.com·15h·
Discuss: Hacker News
🌐WARC Forensics
Gaps in our knowledge of ancient Rome could be filled by AI
bbc.com·1d
🤖AI Paleography
Show HN: Unied Lightweight Terminal Code and Text Editor with Advanced Commands
news.ycombinator.com·16h·
Discuss: Hacker News
📺Terminal UI
A reckless introduction to Hindley-Milner type inference
reasonableapproximation.net·3d·
Discuss: Lobsters, r/programming
🔤Type Theory
The AI Safety Puzzle Everyone Avoids: How To Measure Impact, Not Intent.
lesswrong.com·2d·
Discuss: Hacker News
✨Effect Handlers
Weak baselines and reporting biases lead to overoptimism in ML for fluid PDEs
arxiv.org·1d·
Discuss: Hacker News
🧠Machine Learning
A Preview of Python 3.14 Release: 7 Major New Features You Must Know
dev.to·18h·
Discuss: DEV
🦀Rust Macros
Data-Driven Adaptive Gradient Recovery for Unstructured Finite Volume Computations
arxiv.org·1d
🌀Differential Geometry
PRIDE -- Parameter-Efficient Reduction of Identity Discrimination for Equality in LLMs
arxiv.org·3d
🌀Brotli Dictionary
DFQ-ViT: Data-Free Quantization for Vision Transformers without Fine-tuning
arxiv.org·2d
📊Quantization
Purchase and Production Optimization in a Meat Processing Plant
arxiv.org·1d
📈Linear programming
SenseSeek Dataset: Multimodal Sensing to Study Information Seeking Behaviors
arxiv.org·2d
🧭Content Discovery
The calculus of variations of the Transformer on the hyperspherical tangent bundle
arxiv.org·2d
🌀Differential Geometry
Bipartite Patient-Modality Graph Learning with Event-Conditional Modelling of Censoring for Cancer Survival Prediction
arxiv.org·1d
🧠Machine Learning
Self-Contradiction as Self-Improvement: Mitigating the Generation-Understanding Gap in MLLMs
arxiv.org·1d
💻Local LLMs
Beyond Binary Rewards: Training LMs to Reason About Their Uncertainty
arxiv.org·1d
🧠Intelligence Compression
Machine Learning Fundamentals: feature engineering project
dev.to·1d·
Discuss: DEV
🧠Machine Learning
To Trust or Not to Trust: On Calibration in ML-based Resource Allocation for Wireless Networks
arxiv.org·23h
🧠Machine Learning
Bolt.new top 50 AI driven app builders (until 51 go live)
dev.to·2h·
Discuss: DEV
🌀Brotli Internals
Enhancing Uber's Customer Experience Through Machine Learning: Insights from Harvard's Case Studies
dev.to·2h·
Discuss: DEV
🧠Machine Learning