• Bio
  • Publications
  • Selected Projects
  • Experience
  • Recent & Upcoming Talks
    • Example Talk
  • Courses
    • Hugo Blox
      • Getting Started
      • Guide
        • Project Structure
        • Configuration
        • Formatting
          • Embed Media
          • Buttons
          • Callouts
          • Cards
          • Spoilers
          • Steps
      • Reference
        • Customization
        • Internationalization (i18n)
  • Publications
    • Provable Emergence of Deep Neural Collapse and Low-Rank Bias in $L^2$-Regularized Nonlinear Networks
    • dEBORA: Efficient Bilevel Optimization-based low-Rank Adaptation
    • GeoLoRA: Geometric integration for parameter-efficient fine-tuning
    • Geometry-aware training of factorized layers in tensor Tucker format
    • Low-Rank Adversarial PGD Attack
    • Robust low-rank training via approximate orthonormal constraints
    • HIJACK: Learning-based Strategies for Sound Classification Robustness to Adversarial Noise
    • Low-rank lottery tickets: finding efficient low-rank neural networks via matrix differential equations
  • Projects
    • Pandas
    • PyTorch
    • scikit-learn
  • Experience

scikit-learn

Oct 26, 2023 · 1 min read
Site

scikit-learn is a Python module for machine learning built on top of SciPy and is distributed under the 3-Clause BSD license.

Last updated on Oct 26, 2023
Hugo HugoBlox Markdown
Emanuele Zangrando
Authors
Emanuele Zangrando
PhD Student

← PyTorch Oct 26, 2023

Made with Hugo Blox Builder. Build your site →