- AI · arxiv/cs.LG · 8 min
Theory for learning blind inverse problems with finite samples
Researchers establish sample complexity bounds and optimal estimators for blind inverse problems using linear minimum mean square estimation framework.
April 21, 2026 Read → → - AI · arxiv/cs.LG · 8 min
Chain-of-Thought Supervision Eliminates Sample Complexity Growth
New theoretical analysis shows intermediate reasoning steps remove dependence on generation length, while end-to-end learning scales unpredictably with sequence depth.
April 21, 2026 Read → → - AI · arxiv/cs.LG · 8 min
Formalizing How Much Data Proves a Learning Model Right
Researchers formalize identifying information—the bits needed to confirm or reject a hypothesis—bridging information theory with practical sample complexity.
April 17, 2026 Read → →