Research map / Learning theory and algorithms / Prediction and decision losses
Towards Provably Unlearnable Examples via Bayes Error Optimization
Read the paperCheck your idea against 108,967 papers
AI-extracted summary. Written by AI from the paper's title only (no summary yet). Numbers and claims can be wrong or missing context, so check the paper before you cite or build on it.
Closest papers by meaning
- How Far Are We from True Unlearnability? (ICLR 2025 · similarity 0.89)
- What makes unlearning hard and what to do about it (NeurIPS 2024 · similarity 0.85)
- Unlearning or Obfuscating? Jogging the Memory of Unlearned LLMs via Benign Relearning (ICLR 2025 · similarity 0.85)
- One for All: A Universal Generator for Concept Unlearnability via Multi-Modal Alignment (ICML 2024 · similarity 0.85)
- Provable unlearning in topic modeling and downstream tasks (ICLR 2025 · similarity 0.85)
- Stable Unlearnable Example: Enhancing the Robustness of Unlearnable Examples via Stable Error-Minimizing Noise (AAAI 2024 · similarity 0.85)
Writing a paper in this area? scime draft is a free LaTeX editor with AI included, real-time co-authors and a check of your references and venue rules before you submit. It also imports OpenAI Prism projects.
