📊 Quantization

Model Compression, Neural Networks, Precision Reduction, Efficient Inference

SlimMoE: Structured Compression of Large MoE Models via Expert Slimming and Distillation
arxiv.org·1d
⚡Modern Compression
A Briefing on Logistic Regression
blog.engora.com·1h·
Discuss: Hacker News
🧠Machine Learning
DRIFT: Data Reduction via Informative Feature Transformation- Generalization Begins Before Deep Learning starts
arxiv.org·10h
🧠Machine Learning
ML in the Home
blog.raymond.burkholder.net·1d
📈Time Series
Machine Learning Fundamentals: accuracy with python
dev.to·22h·
Discuss: DEV
👁️Observatory Systems
Quantum-Classical Hybrid Quantized Neural Network
arxiv.org·1d
🕸️Tensor Networks
The Bitter Lesson is coming for Tokenization
lucalp.dev·1d·
Discuss: Lobsters, Hacker News, r/programming
🔗Monadic Parsing
NestQuant: Post-Training Integer-Nesting Quantization for On-Device DNN
arxiv.org·1d
🧠Machine Learning
Ask HN: Feedback on "QSS" – A Quantized Vector Search Engine in C
news.ycombinator.com·1d·
Discuss: Hacker News
🗂️Vector Databases
Scaling Pinterest ML Infrastructure with Ray: From Training to End-to-End ML Pipelines
medium.com·22h·
Discuss: Hacker News
🧮Z3 Applications
The first CNN for playing Scrabble – a game of imperfect information
cesardelsolar.com·2d·
Discuss: Hacker News
🔲Cellular Automata
Greedy Is Good. Less Greedy May Be Better
gojiberries.io·13h·
Discuss: Hacker News
🧮Kolmogorov Complexity
A Qubit-Efficient Hybrid Quantum Encoding Mechanism for Quantum Machine Learning
arxiv.org·10h
⚛️Quantum Codes
Kernel Limit of Recurrent Neural Networks Trained on Ergodic Data Sequences
arxiv.org·1d
🧠Neural Codecs
Google/Videoprism
huggingface.co·15h·
Discuss: Hacker News
📊Learned Metrics
Fully lifted \emph{blirp} interpolation -- a large deviation view
arxiv.org·10h
🌀Fractal Compression
Running 🤖 GPT-Style Transformers on a $5 Microcontroller 🎛️ (TinyML 2.0 Era)
dev.to·1d·
Discuss: DEV
💻Local LLMs
Safe Pruning LoRA: Robust Distance-Guided Pruning for Safety Alignment in Adaptation of LLMs
arxiv.org·10h
💻Local LLMs
Deformable Medical Image Registration with Effective Anatomical Structure Representation and Divide-and-Conquer Network
arxiv.org·10h
🌀Differential Geometry
[D] Applying COCONUT continuous reasoning into a learnt linear layer that produces sampling parameters (temp, top-k, top-p, etc.) for the current token?
reddit.com·1d·
Discuss: r/MachineLearning
💻Local LLMs