ML in the Home
blog.raymond.burkholder.net·1d
📈Time Series
Video Compression for Spatiotemporal Earth System Data
arxiv.org·14h
📊Rate-Distortion Theory
The Bitter Lesson is coming for Tokenization
lucalp.dev·1d·
Discuss: Lobsters, Hacker News, r/programming
🔗Monadic Parsing
A large deviation view of \emph{stationarized} fully lifted blirp interpolation
arxiv.org·14h
📐Compression Bounds
Choice of Scoring Rules for Indirect Elicitation of Properties with Parametric Assumptions
arxiv.org·1d
👑Coq Tactics
Ask HN: Feedback on "QSS" – A Quantized Vector Search Engine in C
news.ycombinator.com·1d·
Discuss: Hacker News
🗂️Vector Databases
AMF-MedIT: An Efficient Align-Modulation-Fusion Framework for Medical Image-Tabular Data
arxiv.org·14h
🤖Advanced OCR
Greedy Is Good. Less Greedy May Be Better
gojiberries.io·17h·
Discuss: Hacker News
🧮Kolmogorov Complexity
Bitmasking for Granular Backend RBAC: A Beginner's Guide
dev.to·5h·
Discuss: DEV
🔐Homomorphic Encryption
"I understand why I got this grade": Automatic Short Answer Grading with Feedback
arxiv.org·1d
🧠Intelligence Compression
Show HN: TableSprint- Supabase alternative with vibe coding features
tablesprint.com·15h·
Discuss: Hacker News
📲Digitization
New: Improve Apache Iceberg query performance in Amazon S3 with sort and z-order compaction
aws.amazon.com·21h
🔄Burrows-Wheeler
Code Rate Optimization via Neural Polar Decoders
arxiv.org·2d
🧠Neural Codecs
🧠 Solving LeetCode Until I Become Top 1% — Day `30`
dev.to·10h·
Discuss: DEV
📐Error Bounds
From Zero to One: A Complete Guide to Implementing WeChat Sharing in HarmonyOS
dev.to·9h·
Discuss: DEV
⚡Modern Compression
Probabilistic and reinforced mining of association rules
arxiv.org·1d
🧠Learned Indexes
SlimMoE: Structured Compression of Large MoE Models via Expert Slimming and Distillation
arxiv.org·1d
⚡Modern Compression
A Lisp adventure on the calm waters of the dead C (2021)
mihaiolteanu.me·1d·
Discuss: Lobsters, Hacker News, r/programming
🔗Lisp
Machine Learning Fundamentals: accuracy with python
dev.to·1d·
Discuss: DEV
👁️Observatory Systems
LVPNet: A Latent-variable-based Prediction-driven End-to-end Framework for Lossless Compression of Medical Images
arxiv.org·1d
🧠Neural Compression