📈 Time Series

Temporal Data, Compression Algorithms, Forecasting, Storage Optimization

Real-time AI Unleashed: The Power of Time-Series and Vector Database Synergy
dev.to·1d·
Discuss: DEV
⏳Temporal Databases
ML in the Home
blog.raymond.burkholder.net·1d
🧠Machine Learning
Data Compression with Relative Entropy Coding
arxiv.org·2d
📐Compression Mathematics
Deep Dive into Databend UDF, implementing your data solutions with Python, WASM
databend.com·21m·
Discuss: Hacker News
📋DFDL
Introduction to the Fundamentals of Amazon Redshift
redshift-observatory.ch·5h
🗃️Database Storage
LSFMM+BPF 2025 reporting complete
lwn.net·54m
📦METS Standards
Agentic AI: Implementing Long-Term Memory
towardsdatascience.com·18h
💾Persistence Strategies
Beyond Static Models: Hypernetworks for Adaptive and Generalizable Forecasting in Complex Parametric Dynamical Systems
arxiv.org·10h
⚡Incremental Computation
Why Agentic Flows Need Distributed-Systems Discipline
temporal.io·21h·
Discuss: Hacker News
⚙️TLA+
No-code data preparation for time series forecasting using Amazon SageMaker Canvas
aws.amazon.com·1d
🌊Streaming Systems
From Zero to One: A Complete Guide to Implementing WeChat Sharing in HarmonyOS
dev.to·6h·
Discuss: DEV
⚡Modern Compression
Kumo Surfaces Structured Data Patterns Generative AI Misses
thenewstack.io·32m
📊Graph Databases
Machine Learning Fundamentals: accuracy with python
dev.to·23h·
Discuss: DEV
👁️Observatory Systems
Ask HN: Feedback on "QSS" – A Quantized Vector Search Engine in C
news.ycombinator.com·1d·
Discuss: Hacker News
🗂️Vector Databases
Probabilistic and reinforced mining of association rules
arxiv.org·1d
🧠Learned Indexes
Floating-Point Data Transformation for Lossless Compression
arxiv.org·1d
🌊Streaming Compression
How much slower is random access, really?
samestep.com·1d·
Discuss: Hacker News
📼Tape Encoding
Azure Fundamentals: Microsoft.TimeSeriesInsights
dev.to·1d·
Discuss: DEV
🔗Data Provenance
SlimMoE: Structured Compression of Large MoE Models via Expert Slimming and Distillation
arxiv.org·1d
⚡Modern Compression
Emotion Detection on User Front-Facing App Interfaces for Enhanced Schedule Optimization: A Machine Learning Approach
arxiv.org·10h
🎛️Feed Filtering