Kernelised covariance matrices, dimension reduction and imbalanced spectral clustering
arXiv:2610.33177v1 Announce Type: new Abstract: The Gaussian Mixture Model (abbrv. GMM) is a classic generative model for clustered data, for which spectral clustering based on dimension reduction via PCA has been an effective framework. In this work, we investigate kernelised covariance matrices a…
Read the full story at arXiv stat.ML ↗
Timeline · 1 report
- 2026-10-27 04:00 · arXiv stat.ML
Kernelised covariance matrices, dimension reduction and imbalanced spectral clustering
More stories
- Moonshot AI launches Kimi K3.1 Pro with better coding skills, reduced cyber risks — Mint AI
- Meta announces $95B offering to fund AI — Semafor Technology
- Introducing GPT-6.1 Terra — OpenAI News
- Anthropic's Claude bypassed a paywall to access Georgia voter data without authorization — Axios AI+
- Microsoft offers buyouts to 60,000 employees — The Verge AI
- OpenAI announces three breakthroughs in computer science, math, and physics, including that the Exponential Time Hypothesis, a longstanding conjecture, is false (OpenAI) — Techmeme
- Anthropic’s IPO filing lays out a plan to ‘revolutionize every area of human endeavor' with AI — The Verge AI
- Anthropic warns of 'catastrophic risk' to humankind ahead of blockbuster share listing — BBC Technology
Get the daily brief of stories like this at 6:30 every morning →