AINewsnow

Diagonalized Attention for Individualized Regression: Latent-Row Localization and Prediction

arXiv:2609.21320v1 Announce Type: new Abstract: Modern text and image representations are often matrix-valued, with rows corresponding to tokens, patches, or other local feature vectors. Predictive information is often sparse but sample-specific, making classical sparse regression methods with a co…

Read the full story at arXiv stat.ML ↗

Timeline · 1 report

  1. 2026-09-21 04:00 · arXiv stat.ML
    Diagonalized Attention for Individualized Regression: Latent-Row Localization and Prediction

More stories

  1. Gemini Hacked Three Companies in First Known Breakout by Google’s AI — Wall Street Journal Technology
  2. Introducing Kimi K3 on Amazon Bedrock — AWS Machine Learning Blog
  3. Introducing Amazon SageMaker HyperPod Inference Gateway — AWS Machine Learning Blog
  4. Anthropic, OpenAI, SpaceXAI, Google sued over call to ‘pace’ AI development — Politico Technology
  5. NVIDIA CEO Jensen Huang rejects ‘AI will end the world’ claim, yet cautions ‘we should go as fast as we can but...’ — Mint AI
  6. AI hallucination of Chinese nuclear components almost led to US military attack — Ars Technica AI
  7. The new AgentCore runtime: Elastic, optimized, and consistently fast starts — AWS Machine Learning Blog
  8. Qwen Image 2.1 PR to ComfyUI — r/StableDiffusion

Get the daily brief of stories like this at 6:30 every morning →