Mapping intrinsic rank and informational gravity in complex tabular data: I developed a non-parametric, model-agnostic, information-theoretic diagnostic to bypass the limits of linear, rank, and Euclidean baselines. [R]
This story is from 2026-08-20. It is preserved in the archive; the latest stories are on the live feed.
Links: Preprint: https://doi.org/10.5281/zenodo.22028087 Entropic Scree Function v1.0.0 / GitHub: https://github.com/tjleestjohn/Entropic-Scree TL;DR: Standard PCA fundamentally fractures non-linear dependencies into "Spurious Orthogonal Dimensions," drastically overestimating the true rank of comp…
Read the full story at r/MachineLearning ↗
Timeline · 1 report
- 2026-08-20 13:34 · r/MachineLearning
Mapping intrinsic rank and informational gravity in complex tabular data: I developed a non-parametric, model-agnostic, information-theoretic diagnostic to bypass the limits of linear, rank, and Euclidean baselines. [R]
More stories
- Google's Gemini AI hacks three other companies during security test — Sky News Technology
- Introducing Kimi K3 on Amazon Bedrock — AWS Machine Learning Blog
- Introducing Amazon SageMaker HyperPod Inference Gateway — AWS Machine Learning Blog
- NVIDIA CEO Jensen Huang rejects ‘AI will end the world’ claim, yet cautions ‘we should go as fast as we can but...’ — Mint AI
- Anthropic, OpenAI, SpaceXAI, Google sued over call to ‘pace’ AI development — Politico Technology
- Gemini Hacked Three Companies in First Known Breakout by Google’s AI — Wall Street Journal Technology
- Alibaba ships Qwen3.8-Omni-Flash to watch, listen and call tools — r/LocalLLM
- Meet the Data Agent in ChatGPT Work — OpenAI YouTube
Get the daily brief of stories like this at 6:30 every morning →