- AI · arxiv/cs.AI · 8 min
Q-Value Iteration Finds Optimal Actions Faster Than Theory Predicts
Lee's switching system analysis reveals Q-VI reaches practical optimality in finite time, with convergence rates potentially faster than the classical discount factor bound.
April 22, 2026 Read → → - AI · arxiv/cs.LG · 8 min
INT4 Quantization Fails After FP32 Convergence in Predictable Phases
Post-training quantization assumes converged models are ready to compress, but INT4 quantization collapses in a three-phase pattern tied to weight updates, not learning rate decay.
April 17, 2026 Read → →